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#sister-miriam-joseph #trivium

Question

There are four internal senses:

The**imagination**,

The**[...]**,

The common or central or**synthesizing sense**,

and**instinct**.

The

The

The common or central or

and

Answer

sensuous memory

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repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

There are four internal senses: The imagination , The sensuous memory , The common or central or synthesizing sense , and instinct .

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Question

risk for contrast-induced nephropathy (CIN), and administration of intravenous isotonic saline [...] 3 to 12 hours before the procedure and continued for 6 to 24 hours afterward has been shown to decrease the incidence of CIN in high-risk patients.

Answer

(1-1.5 mL/kg/h)

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repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

risk for contrast-induced nephropathy (CIN), and administration of intravenous isotonic saline (1-1.5 mL/kg/h) 3 to 12 hours before the procedure and continued for 6 to 24 hours afterward has been shown to decrease the incidence of CIN in high-risk patients.

Question

risk for contrast-induced nephropathy (CIN), and administration of intravenous isotonic saline (1-1.5 mL/kg/h) [...] hours before the procedure and continued for 6 to 24 hours afterward has been shown to decrease the incidence of CIN in high-risk patients.

Answer

3 to 12

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repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

risk for contrast-induced nephropathy (CIN), and administration of intravenous isotonic saline (1-1.5 mL/kg/h) 3 to 12 hours before the procedure and continued for 6 to 24 hours afterward has been shown to decrease the incidence of CIN in high-risk patients.

Question

risk for contrast-induced nephropathy (CIN), and administration of intravenous isotonic saline (1-1.5 mL/kg/h) 3 to 12 hours before the procedure and continued for [...] hours afterward has been shown to decrease the incidence of CIN in high-risk patients.

Answer

6 to 24

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repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

risk for contrast-induced nephropathy (CIN), and administration of intravenous isotonic saline (1-1.5 mL/kg/h) 3 to 12 hours before the procedure and continued for 6 to 24 hours afterward has been shown to decrease the incidence of CIN in high-risk patients.

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Question

Risk factors for contrast indused nephroathy include

Answer

age older than 75 years, diabetes mellitus, chronic kidney disease, conditions of decreased renal perfusion, and concurrent use of nephrotoxic drugs.

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repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

Risk factors include age older than 75 years, diabetes mellitus, chronic kidney disease, conditions of decreased renal perfusion, and concurrent use of nephrotoxic drugs.

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Question

discontinuing omeprazole, repeat kidney function testing in [...] days is the most appropriate management for this patient with acute interstitial nephritis (AIN).

Answer

5 to 7

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scheduled repetition interval | last repetition or drill |

discontinuing omeprazole, repeat kidney function testing in 5 to 7 days is the most appropriate management for this patient with acute interstitial nephritis (AIN).

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Question

Drug-induced AIN is characterized by a slowly increasing serum creatinine [...] days after exposure; however, it can occur within 1 day of exposure if the patient has been exposed previously. Drug-induced AIN can also occur months after exposure, often with NSAIDs and proton pump inhibitors (PPIs)

Answer

7 to 10

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repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

Drug-induced AIN is characterized by a slowly increasing serum creatinine 7 to 10 days after exposure; however, it can occur within 1 day of exposure if the patient has been exposed previously. Drug-induced AIN can also occur months after exposure, often with NSAI

Question

Drug-induced AIN is characterized by a slowly increasing serum creatinine 7 to 10 days after exposure; however, it can occur within [...] of exposure if the patient has been exposed previously. Drug-induced AIN can also occur months after exposure, often with NSAIDs and proton pump inhibitors (PPIs)

Answer

1 day

status | not learned | measured difficulty | 37% [default] | last interval [days] | |||
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repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

Drug-induced AIN is characterized by a slowly increasing serum creatinine 7 to 10 days after exposure; however, it can occur within 1 day of exposure if the patient has been exposed previously. Drug-induced AIN can also occur months after exposure, often with NSAIDs and proton pump inhibitors (PPIs)

Question

Drug-induced AIN is characterized by a slowly increasing serum creatinine 7 to 10 days after exposure; however, it can occur within 1 day of exposure if the patient has been exposed previously. Drug-induced AIN can also occur [...] after exposure, often with NSAIDs and proton pump inhibitors (PPIs)

Answer

months

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repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

y>Drug-induced AIN is characterized by a slowly increasing serum creatinine 7 to 10 days after exposure; however, it can occur within 1 day of exposure if the patient has been exposed previously. Drug-induced AIN can also occur months after exposure, often with NSAIDs and proton pump inhibitors (PPIs)<body><html>

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Question

AIN may be asymptomatic or present with mild, nonspecific symptoms; only 10% to 30% have the classic triad of [...]

Answer

fever, rash, and eosinophilia.

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repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

AIN may be asymptomatic or present with mild, nonspecific symptoms; only 10% to 30% have the classic triad of fever, rash, and eosinophilia.

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#reading-8-statistical-concepts-and-market-returns

Question

Religious preference, race, and sex are all examples of **[...]** scales

Answer

nominal scales.

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st level of measurement. It consists of assigning items to groups or categories. No quantitative information is conveyed and no ordering (ranking) of the items is implied. Nominal scales are qualitative rather than quantitative. <span>Religious preference, race, and sex are all examples of nominal scales. Another example is portfolio managers categorized as value or growth style will have a scale of 1 for value and 2 for growth. Frequency distributions are usually used to analyze data me

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#reading-8-statistical-concepts-and-market-returns

Question

A **[...]** is a tabular display of data categorized into a small number of non-overlapping intervals.

Answer

status | not learned | measured difficulty | 37% [default] | last interval [days] | |||
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repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

ency distribution. An interval, also called a class, is a set of values within which an observation falls. Each interval has a lower limit and an upper limit. Intervals must be all-inclusive and non-overlapping. <span>A frequency distribution is a tabular display of data categorized into a small number of non-overlapping intervals. Note that: Each observation can only lie in one interval. The total number of intervals will incorporate the whole population. The range for an interval is unique. This mean

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#reading-8-statistical-concepts-and-market-returns

Question

An **interval **is also called a **[...]**

Answer

status | not learned | measured difficulty | 37% [default] | last interval [days] | |||
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repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

with individual numbers becomes laborious and messy. In such circumstances, it is neater and more convenient to summarize results into what is known as a frequency table. The data in the display is called a frequency distribution. <span>An interval, also called a class, is a set of values within which an observation falls. Each interval has a lower limit and an upper limit. Intervals must be all-inclusive and non-overlapping. A frequency distribution is a tabular display of data categor

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#reading-8-statistical-concepts-and-market-returns

Question

An **[...]** is a set of values within which an observation falls.

Answer

status | not learned | measured difficulty | 37% [default] | last interval [days] | |||
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repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

with individual numbers becomes laborious and messy. In such circumstances, it is neater and more convenient to summarize results into what is known as a frequency table. The data in the display is called a frequency distribution. <span>An interval, also called a class, is a set of values within which an observation falls. Each interval has a lower limit and an upper limit. Intervals must be all-inclusive and non-overlapping. A frequency distribution is a tabular display of data categor

#reading-8-statistical-concepts-and-market-returns

A **frequency distribution** is a tabular display of data categorized into a small number of non-overlapping intervals. Note that:

- Each observation can only lie in one interval.
- The total number of intervals will incorporate the whole population.
- The range for an interval is unique. This means a value (observation) can only fall into one interval.

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last reprioritisation on | reading queue position [%] | |||

started reading on | finished reading on |

ency distribution. An interval, also called a class, is a set of values within which an observation falls. Each interval has a lower limit and an upper limit. Intervals must be all-inclusive and non-overlapping. <span>A frequency distribution is a tabular display of data categorized into a small number of non-overlapping intervals. Note that: Each observation can only lie in one interval. The total number of intervals will incorporate the whole population. The range for an interval is unique. This means a value (observation) can only fall into one interval. It is important to consider the number of intervals to be used. If too few intervals are used, too much data may be summarized and we may lose important characteristics; if too ma

#reading-8-statistical-concepts-and-market-returns

In a **frequency distribution **It is important to consider the number of intervals to be used. If too few intervals are used, too much data may be summarized and we may lose important characteristics; if too many intervals are used, we may not summarize enough.

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that: Each observation can only lie in one interval. The total number of intervals will incorporate the whole population. The range for an interval is unique. This means a value (observation) can only fall into one interval. <span>It is important to consider the number of intervals to be used. If too few intervals are used, too much data may be summarized and we may lose important characteristics; if too many intervals are used, we may not summarize enough. A frequency distribution is constructed by dividing the scores into intervals and counting the number of scores in each interval. The actual number of scores and the percent

#reading-8-statistical-concepts-and-market-returns

A frequency distribution is constructed by dividing the scores into intervals and counting the number of scores in each interval. The actual number of scores and the percentage of scores in each interval are displayed. This helps in the analysis of large amount of statistical data, and works with all types of measurement scales.

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It is important to consider the number of intervals to be used. If too few intervals are used, too much data may be summarized and we may lose important characteristics; if too many intervals are used, we may not summarize enough. <span>A frequency distribution is constructed by dividing the scores into intervals and counting the number of scores in each interval. The actual number of scores and the percentage of scores in each interval are displayed. This helps in the analysis of large amount of statistical data, and works with all types of measurement scales. Absolute frequency is the actual number of observations in a given interval. Relative frequency is the result of dividing the absolute frequency of e

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#reading-8-statistical-concepts-and-market-returns

Question

Answer

status | not learned | measured difficulty | 37% [default] | last interval [days] | |||
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repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

of scores in each interval. The actual number of scores and the percentage of scores in each interval are displayed. This helps in the analysis of large amount of statistical data, and works with all types of measurement scales. <span>Absolute frequency is the actual number of observations in a given interval. Relative frequency is the result of dividing the absolute frequency of each return interval by the total number of observations. Cumulative absol

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#reading-8-statistical-concepts-and-market-returns

Question

Answer

status | not learned | measured difficulty | 37% [default] | last interval [days] | |||
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repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

al are displayed. This helps in the analysis of large amount of statistical data, and works with all types of measurement scales. Absolute frequency is the actual number of observations in a given interval. <span>Relative frequency is the result of dividing the absolute frequency of each return interval by the total number of observations. Cumulative absolute frequency and cumulative relative frequency are the results from cumulating the absolute and relative frequencies as we move from the first to the l

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#reading-8-statistical-concepts-and-market-returns

Question

Answer

status | not learned | measured difficulty | 37% [default] | last interval [days] | |||
---|---|---|---|---|---|---|---|

repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

olute frequency is the actual number of observations in a given interval. Relative frequency is the result of dividing the absolute frequency of each return interval by the total number of observations. <span>Cumulative absolute frequency and cumulative relative frequency are the results from cumulating the absolute and relative frequencies as we move from the first to the last interval. The following steps are required when organizing data into a frequency distribution together with suggestions on constructing the frequency distribution. Identify the

#reading-8-statistical-concepts-and-market-returns

The following steps are required when organizing data into a frequency distribution together with suggestions on constructing the frequency distribution.

- Identify the highest and lowest values of the observations.
- Setup classes (groups into which data is divided). The classes must be mutually exclusive and of equal size.
- Add up the number of observations and assign each observation to its class.
- Count the number of observations in each class. This is called the class frequency.

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by the total number of observations. Cumulative absolute frequency and cumulative relative frequency are the results from cumulating the absolute and relative frequencies as we move from the first to the last interval. <span>The following steps are required when organizing data into a frequency distribution together with suggestions on constructing the frequency distribution. Identify the highest and lowest values of the observations. Setup classes (groups into which data is divided). The classes must be mutually exclusive and of equal size. Add up the number of observations and assign each observation to its class. Count the number of observations in each class. This is called the class frequency. Data can be divided into two types: discrete and continuous. Discrete: The values in the data set can be counted. There are distinct spaces between the values, such as

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#reading-8-statistical-concepts-and-market-returns

Question

Data can be divided into two types: **[...]** and **[...]**

Answer

discrete

continuous.

continuous.

status | not learned | measured difficulty | 37% [default] | last interval [days] | |||
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repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

t be mutually exclusive and of equal size. Add up the number of observations and assign each observation to its class. Count the number of observations in each class. This is called the class frequency. <span>Data can be divided into two types: discrete and continuous. Discrete: The values in the data set can be counted. There are distinct spaces between the values, such as the number of children in a family or the number of shares compris

#reading-8-statistical-concepts-and-market-returns

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mber of observations and assign each observation to its class. Count the number of observations in each class. This is called the class frequency. Data can be divided into two types: discrete and continuous. <span>Discrete: The values in the data set can be counted. There are distinct spaces between the values, such as the number of children in a family or the number of shares comprising an index. Continuous: The values in the data set can be measured. There are normally lots of decimal places involved and (theoretically, at least) there are no gaps between permissible values (i.

#reading-8-statistical-concepts-and-market-returns

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ed into two types: discrete and continuous. Discrete: The values in the data set can be counted. There are distinct spaces between the values, such as the number of children in a family or the number of shares comprising an index. <span>Continuous: The values in the data set can be measured. There are normally lots of decimal places involved and (theoretically, at least) there are no gaps between permissible values (i.e., all values can be included in the data set). Examples would include the height of a person and the time to complete an assignment. These values can be measured using sufficiently accurate tools to numerous decimal places. There are two methods that graphically represent continuous data: histograms and frequency polygons. 1. A histogram is a bar chart that displays a frequency distributi

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Question

There are two methods that graphically represent continuous data: **[...]** and **[...]**

Answer

histograms

frequency polygons.

frequency polygons.

status | not learned | measured difficulty | 37% [default] | last interval [days] | |||
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repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

values (i.e., all values can be included in the data set). Examples would include the height of a person and the time to complete an assignment. These values can be measured using sufficiently accurate tools to numerous decimal places. <span>There are two methods that graphically represent continuous data: histograms and frequency polygons. 1. A histogram is a bar chart that displays a frequency distribution. It is constructed as follows: The class frequencies are shown on the vertical (y) axis (by

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#reading-7-discounted-cashflows-applications

Question

Is Bank discount yield a meaningful measure of the return on investment?

Answer

not

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repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

unt basis D = the dollar discount, which is equal to the difference between the face value of the bill, F, and its purchase price, P t = the number of days remaining to maturity 360 = the bank convention of the number of days in a year. <span>Bank discount yield is not a meaningful measure of the return on investment because: It is based on the face value, not on the purchase price. Instead, return on investment should be measured based on cost of investment. It is annualized using a 360-day year, not a 365-day year. It annualizes with simple interest and ignores the effect of interest on interest (compound interest). Holding period yield (HPY) is the return earned by an investor if the money market instrument is held until maturity: P 0 =

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#reading-8-statistical-concepts-and-market-returns

Question

Answer

status | not learned | measured difficulty | 37% [default] | last interval [days] | |||
---|---|---|---|---|---|---|---|

repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

mber of observations and assign each observation to its class. Count the number of observations in each class. This is called the class frequency. Data can be divided into two types: discrete and continuous. <span>Discrete: The values in the data set can be counted. There are distinct spaces between the values, such as the number of children in a family or the number of shares comprising an index. Continuous: The values in the data set can be measu

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#reading-8-statistical-concepts-and-market-returns

Question

Answer

status | not learned | measured difficulty | 37% [default] | last interval [days] | |||
---|---|---|---|---|---|---|---|

repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

ed into two types: discrete and continuous. Discrete: The values in the data set can be counted. There are distinct spaces between the values, such as the number of children in a family or the number of shares comprising an index. <span>Continuous: The values in the data set can be measured. There are normally lots of decimal places involved and (theoretically, at least) there are no gaps between permissible values (i.e., all values can be included in the data set). Example

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#reading-8-statistical-concepts-and-market-returns

Question

A **[...]** is a bar chart that displays a frequency distribution.

Answer

histogram

status | not learned | measured difficulty | 37% [default] | last interval [days] | |||
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repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

me to complete an assignment. These values can be measured using sufficiently accurate tools to numerous decimal places. There are two methods that graphically represent continuous data: histograms and frequency polygons. 1. <span>A histogram is a bar chart that displays a frequency distribution. It is constructed as follows: The class frequencies are shown on the vertical (y) axis (by the heights of bars drawn next to each other). The classes (intervals) are shown

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#reading-8-statistical-concepts-and-market-returns

Question

In a histogram the **[...]** are shown on the vertical (y) axis

Answer

class frequencies

(by the heights of bars drawn next to each other).

(by the heights of bars drawn next to each other).

status | not learned | measured difficulty | 37% [default] | last interval [days] | |||
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repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

al places. There are two methods that graphically represent continuous data: histograms and frequency polygons. 1. A histogram is a bar chart that displays a frequency distribution. It is constructed as follows: <span>The class frequencies are shown on the vertical (y) axis (by the heights of bars drawn next to each other). The classes (intervals) are shown on the horizontal (x) axis. There is no space between the bars. From a histogram, we can see quickly where most of the observa

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#reading-8-statistical-concepts-and-market-returns

Question

In a frequency histogram **[...]** are shown on the horizontal (x) axis.

Answer

the classes (intervals)

status | not learned | measured difficulty | 37% [default] | last interval [days] | |||
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repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

polygons. 1. A histogram is a bar chart that displays a frequency distribution. It is constructed as follows: The class frequencies are shown on the vertical (y) axis (by the heights of bars drawn next to each other). <span>The classes (intervals) are shown on the horizontal (x) axis. There is no space between the bars. From a histogram, we can see quickly where most of the observations lie. The shapes of histograms will vary, depending on th

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#reading-8-statistical-concepts-and-market-returns

Question

How much space is there between the bars of a histogram

Answer

There is no space between the bars

status | not learned | measured difficulty | 37% [default] | last interval [days] | |||
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repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

ays a frequency distribution. It is constructed as follows: The class frequencies are shown on the vertical (y) axis (by the heights of bars drawn next to each other). The classes (intervals) are shown on the horizontal (x) axis. <span>There is no space between the bars. From a histogram, we can see quickly where most of the observations lie. The shapes of histograms will vary, depending on the choice of the size of the interva

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Question

From a histogram, we can see quickly where **[...]**.

Answer

most of the observations lie

status | not learned | measured difficulty | 37% [default] | last interval [days] | |||
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repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

#13; The class frequencies are shown on the vertical (y) axis (by the heights of bars drawn next to each other). The classes (intervals) are shown on the horizontal (x) axis. There is no space between the bars. <span>From a histogram, we can see quickly where most of the observations lie. The shapes of histograms will vary, depending on the choice of the size of the intervals. 2. The frequency polygon is another means of graphically displaying data. It is si

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#reading-8-statistical-concepts-and-market-returns

Question

The shapes of histograms will vary, depending on **[...]**

Answer

the choice of the size of the intervals.

status | not learned | measured difficulty | 37% [default] | last interval [days] | |||
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repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

the heights of bars drawn next to each other). The classes (intervals) are shown on the horizontal (x) axis. There is no space between the bars. From a histogram, we can see quickly where most of the observations lie. <span>The shapes of histograms will vary, depending on the choice of the size of the intervals. 2. The frequency polygon is another means of graphically displaying data. It is similar to a histogram but the bars are replaced by a line joined together. It is constructe

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#reading-8-statistical-concepts-and-market-returns

Question

Besides the histogram, the **[...]** is another means of graphically displaying data.

Answer

frequency polygon

status | not learned | measured difficulty | 37% [default] | last interval [days] | |||
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repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

s. There is no space between the bars. From a histogram, we can see quickly where most of the observations lie. The shapes of histograms will vary, depending on the choice of the size of the intervals. 2. <span>The frequency polygon is another means of graphically displaying data. It is similar to a histogram but the bars are replaced by a line joined together. It is constructed in the following manner: Absolute frequency for each interval is plotted

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Question

In the **[...]** the midpoint of each class (interval) is shown on the horizontal (x) axis.

Answer

Frequency Polygon

status | not learned | measured difficulty | 37% [default] | last interval [days] | |||
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repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

f graphically displaying data. It is similar to a histogram but the bars are replaced by a line joined together. It is constructed in the following manner: Absolute frequency for each interval is plotted on the vertical (y) axis. <span>The midpoint of each class (interval) is shown on the horizontal (x) axis. Neighboring points are connected with a straight line. Unlike a histogram, a frequency polygon adds a degree of continuity to the presentation of the distribution. It

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Question

Unlike a histogram, a frequency polygon adds a degree of **[...]** to the presentation of the distribution.

Answer

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e following manner: Absolute frequency for each interval is plotted on the vertical (y) axis. The midpoint of each class (interval) is shown on the horizontal (x) axis. Neighboring points are connected with a straight line. <span>Unlike a histogram, a frequency polygon adds a degree of continuity to the presentation of the distribution. It is helpful, when drawing a frequency polygon, first to draw a histogram in pencil, then to plot the points and join the lines, and finally to rub out the histogram. In th

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Question

The **[...]** for a class is calculated by dividing the number of observations in a class by the total number of observations and converting this figure to a percentage.

Answer

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first to draw a histogram in pencil, then to plot the points and join the lines, and finally to rub out the histogram. In this way, the histogram can be used as an initial guide to drawing the polygon. <span>The relative frequency for a class is calculated by dividing the number of observations in a class by the total number of observations and converting this figure to a percentage (multiplying the fraction by 100). Simply, relative frequency is the percentage of total observations falling within each interval. It is another way of analyzing data; it tells us, for each class, what proportion (or pe

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Question

Simply, relative frequency is the **[...]** of total observations falling within each interval.

Answer

percentage

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; The relative frequency for a class is calculated by dividing the number of observations in a class by the total number of observations and converting this figure to a percentage (multiplying the fraction by 100). <span>Simply, relative frequency is the percentage of total observations falling within each interval. It is another way of analyzing data; it tells us, for each class, what proportion (or percentage) of data falls in that class. Let's look at an example. The fo

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Question

If, in an examination, your relative frequency column does not sum **[...]**, you know that you have made a mistake.

Answer

to 1 (or 100%)

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st one is -27%. Let's use 6 non-overlapping intervals, each with a width of 10%. The first interval starts at -27% and the last one ends at 33%. Therefore, the entire range of the HPRs is covered. Hint: <span>If, in an examination, your relative frequency column does not sum to 1 (or 100%), you know that you have made a mistake. <span><body><html>

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**Population Mean**

The population mean is the average for a finite population. It is unique; a given population has only one mean.

where:

- N = the number of observations in the entire population
- X
_{i}= the ith observation - Î£X
_{i}= add up X_{i}, where i is from 0 to N

**Sample Mean**

The sample mean is the average for a sample. It is a statistic and is used to estimate the population mean.

where n = the number of observations in the sample

**Arithmetic Mean**

The arithmetic mean is what is commonly called the average. The population mean and sample mean are both examples of the arithmetic mean.

- If the data set encompasses an entire population, the arithmetic mean is called a population mean.
- If the data set includes a sample of values taken from a population, the arithmetic mean is called a sample mean.

This is the most widely used measure of central tendency. When the word "mean" is used without a modifier, it can be assumed to refer to the arithmetic mean. The mean is the sum of all scores divided by the number of scores. It is used to measure the prospective (expected future) performance (return) of an investment over a number of periods.

- All interval and ratio data sets (e.g., incomes, ages, rates of return) have an arithmetic mean.
- All data values are considered and included in the arithmetic mean computation.
- A data set has only one arithmetic mean. This indicates that the mean is unique.
- The arithmetic mean is the only measure of central tendency where the sum of the deviations of each value from the mean is always zero.
**Deviation**from the arithmetic mean is the distance between the mean and an observation in the data set.

The arithmetic mean has the following disadvantages:

- The mean can be affected by extremes, that is, unusually large or small values.
- The mean cannot be determined for an open-ended data set (i.e., n is unknown).

**Geometric Mean**

The geometric mean has three important properties:

- It exists only if all the observations are greater than or equal to zero. In other words, it cannot be determined if any value of the data set is zero or negative.
- If values in the data set are all equal, both the arithmetic and geometric means will be equal to that value.
- It is always less than the arithmetic mean if values in the data set are not equal.

It is typically used when calculating returns over multiple periods. It is a better measure of the compound growth rate of an investment. When returns are variable by period, the geometric mean will always be less than the arithmetic mean. The more dispersed the rates of returns, the greater the difference between the two. This measurement is not as highly influenced by extreme values as the arithmetic mean.

**Weighted Mean**

The weighted mean is computed by weighting each observed value according to its importance. In contrast, the arithmetic mean assigns equal weight to each value. Notice that the return of a portfolio is the weighted mean of the returns of individual

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Question

Answer

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scheduled repetition interval | last repetition or drill |

Measures of central tendency specify where data are centered. They attempt to use a typical value to represent all the observations in the data set. Population Mean The population mean is the average for a finite populatio

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Question

The population mean formula

Answer

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head><head> Measures of central tendency specify where data are centered. They attempt to use a typical value to represent all the observations in the data set. Population Mean The population mean is the average for a finite population. It is unique; a given population has only one mean. where: N = the number of observations in the entire population X i = the ith observation Î£X i = add up X i , where i is from 0 to

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Question

Population mean

where:

- N =
**[...]** - X
_{i}=**[...]** - Î£X
_{i}=**[...]**

Answer

the number of observations in the entire population

the ith observation

add up X_{i}, where i is from 0 to N

the ith observation

add up X

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represent all the observations in the data set. Population Mean The population mean is the average for a finite population. It is unique; a given population has only one mean. <span>where: N = the number of observations in the entire population X i = the ith observation Î£X i = add up X i , where i is from 0 to N Sample Mean The sample mean is the average for a sample. It is a statistic and is used to estimate the population mean.

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Question

**Sample Mean** Formula

Answer

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que; a given population has only one mean. where: N = the number of observations in the entire population X i = the ith observation Î£X i = add up X i , where i is from 0 to N <span>Sample Mean The sample mean is the average for a sample. It is a statistic and is used to estimate the population mean. where n = the number of observations in the sample Arithmetic Mean The arithmetic mean is what is commonly called the a

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Question

The population mean and sample mean are both examples of the **[...]** mean.

Answer

arithmetic

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stic and is used to estimate the population mean. where n = the number of observations in the sample Arithmetic Mean The arithmetic mean is what is commonly called the average. <span>The population mean and sample mean are both examples of the arithmetic mean. If the data set encompasses an entire population, the arithmetic mean is called a population mean. If the data set includes a sample of values taken from a population, the

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Question

If the data set encompasses an entire population, the arithmetic mean is called a **[...]**

Answer

population mean.

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here n = the number of observations in the sample Arithmetic Mean The arithmetic mean is what is commonly called the average. The population mean and sample mean are both examples of the arithmetic mean. <span>If the data set encompasses an entire population, the arithmetic mean is called a population mean. If the data set includes a sample of values taken from a population, the arithmetic mean is called a sample mean. This is the most widely used measure of central tendency.

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Question

If the data set includes a sample of values taken from a population, the arithmetic mean is called a **[...]**

Answer

sample mean.

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thmetic mean is what is commonly called the average. The population mean and sample mean are both examples of the arithmetic mean. If the data set encompasses an entire population, the arithmetic mean is called a population mean. <span>If the data set includes a sample of values taken from a population, the arithmetic mean is called a sample mean. This is the most widely used measure of central tendency. When the word "mean" is used without a modifier, it can be assumed to refer to the arithmetic mean. The

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Question

What is the most widely used measure of central tendency?

Answer

Arithmetic mean

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an. If the data set encompasses an entire population, the arithmetic mean is called a population mean. If the data set includes a sample of values taken from a population, the arithmetic mean is called a sample mean. <span>This is the most widely used measure of central tendency. When the word "mean" is used without a modifier, it can be assumed to refer to the arithmetic mean. The mean is the sum of all scores divided by the number of scores. It is us

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Question

When the word "mean" is used without a modifier, it can be assumed to refer to the **[...]** .

Answer

arithmetic mean

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ulation, the arithmetic mean is called a population mean. If the data set includes a sample of values taken from a population, the arithmetic mean is called a sample mean. This is the most widely used measure of central tendency. <span>When the word "mean" is used without a modifier, it can be assumed to refer to the arithmetic mean. The mean is the sum of all scores divided by the number of scores. It is used to measure the prospective (expected future) performance (return) of an investment over a number of periods

Tags

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Question

All **[...]** and **[...]** (measurement scales) data sets have an arithmetic mean.

Answer

interval

ratio

ratio

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e assumed to refer to the arithmetic mean. The mean is the sum of all scores divided by the number of scores. It is used to measure the prospective (expected future) performance (return) of an investment over a number of periods. <span>All interval and ratio data sets (e.g., incomes, ages, rates of return) have an arithmetic mean. All data values are considered and included in the arithmetic mean computation. A data set has only one arithmetic mean. This indicates that the mean is unique. The arithmetic mean is t

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All data values are considered and included in the arithmetic mean computation.

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r of scores. It is used to measure the prospective (expected future) performance (return) of an investment over a number of periods. All interval and ratio data sets (e.g., incomes, ages, rates of return) have an arithmetic mean. <span>All data values are considered and included in the arithmetic mean computation. A data set has only one arithmetic mean. This indicates that the mean is unique. The arithmetic mean is the only measure of central tendency where the sum of the deviations of each valu

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Question

How many arirhmetic means does a data set have.

Answer

only one arithmetic mean.

his indicates that the mean is unique.

his indicates that the mean is unique.

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(return) of an investment over a number of periods. All interval and ratio data sets (e.g., incomes, ages, rates of return) have an arithmetic mean. All data values are considered and included in the arithmetic mean computation. <span>A data set has only one arithmetic mean. This indicates that the mean is unique. The arithmetic mean is the only measure of central tendency where the sum of the deviations of each value from the mean is always zero. Deviation from the arithmetic mean is the distanc

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Question

The **[...]** is the only measure of central tendency where the sum of the deviations of each value from the mean is always zero.

Answer

arithmetic mean

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d ratio data sets (e.g., incomes, ages, rates of return) have an arithmetic mean. All data values are considered and included in the arithmetic mean computation. A data set has only one arithmetic mean. This indicates that the mean is unique. <span>The arithmetic mean is the only measure of central tendency where the sum of the deviations of each value from the mean is always zero. Deviation from the arithmetic mean is the distance between the mean and an observation in the data set. The arithmetic mean has the following disadvantages: Th

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Question

Answer

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thmetic mean computation. A data set has only one arithmetic mean. This indicates that the mean is unique. The arithmetic mean is the only measure of central tendency where the sum of the deviations of each value from the mean is always zero. <span>Deviation from the arithmetic mean is the distance between the mean and an observation in the data set. The arithmetic mean has the following disadvantages: The mean can be affected by extremes, that is, unusually large or small values. The mean cannot be determi

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Question

The arithmetic mean has the following disadvantages:

- The mean can be
**[...]**

Answer

affected by extremes.

unusually large or small values.

unusually large or small values.

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etic mean is the only measure of central tendency where the sum of the deviations of each value from the mean is always zero. Deviation from the arithmetic mean is the distance between the mean and an observation in the data set. <span>The arithmetic mean has the following disadvantages: The mean can be affected by extremes, that is, unusually large or small values. The mean cannot be determined for an open-ended data set (i.e., n is unknown). Geometric Mean The geometric mean has three important

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Question

The arithmetic mean has the following disadvantages:

- The mean cannot be determined for
**[...]**

Answer

an open-ended data set (i.e., n is unknown).

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etic mean is the only measure of central tendency where the sum of the deviations of each value from the mean is always zero. Deviation from the arithmetic mean is the distance between the mean and an observation in the data set. <span>The arithmetic mean has the following disadvantages: The mean can be affected by extremes, that is, unusually large or small values. The mean cannot be determined for an open-ended data set (i.e., n is unknown). Geometric Mean The geometric mean has three important properties: It exists only if all the observations are greater th

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Question

**Geometric Mean formula**

Answer

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13; The arithmetic mean has the following disadvantages: The mean can be affected by extremes, that is, unusually large or small values. The mean cannot be determined for an open-ended data set (i.e., n is unknown). <span>Geometric Mean The geometric mean has three important properties: It exists only if all the observations are greater than or equal to zero. In othe

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Question

The geometric mean has two important properties:

- It exists
**[...]** - It is always less than the arithmetic mean if values in the data set are not equal.

Answer

only if all the observations are greater than or equal to zero.

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s: The mean can be affected by extremes, that is, unusually large or small values. The mean cannot be determined for an open-ended data set (i.e., n is unknown). Geometric Mean <span>The geometric mean has three important properties: It exists only if all the observations are greater than or equal to zero. In other words, it cannot be determined if any value of the data set is zero or negative. If values in the data set are all equal, both the arithmetic and geometric means will be equal to that value. It is always less than the arithmetic mean if values in the data set are not equal. It is typically used when calculating returns over multiple periods. It is a better measure of the compound growth rate of an investment. When returns are variable by perio

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Question

Which mean is typically used when calculating returns over multiple periods.

Answer

Geometric mean

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f the data set is zero or negative. If values in the data set are all equal, both the arithmetic and geometric means will be equal to that value. It is always less than the arithmetic mean if values in the data set are not equal. <span>It is typically used when calculating returns over multiple periods. It is a better measure of the compound growth rate of an investment. When returns are variable by period, the geometric mean will always be less than the arithmetic mean. The more dispe

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Question

When returns are variable by period, the geometric mean will always be **[...]** than the arithmetic mean.

Answer

less

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value. It is always less than the arithmetic mean if values in the data set are not equal. It is typically used when calculating returns over multiple periods. It is a better measure of the compound growth rate of an investment. <span>When returns are variable by period, the geometric mean will always be less than the arithmetic mean. The more dispersed the rates of returns, the greater the difference between the two. This measurement is not as highly influenced by extreme values as the arithmetic mean.

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Question

The more **[...]** the rates of returns, the greater the difference between Arithmetic and Geometric mean.

Answer

dispersed

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; It is typically used when calculating returns over multiple periods. It is a better measure of the compound growth rate of an investment. When returns are variable by period, the geometric mean will always be less than the arithmetic mean. <span>The more dispersed the rates of returns, the greater the difference between the two. This measurement is not as highly influenced by extreme values as the arithmetic mean. Weighted Mean The weighted mean is computed by weighting each observed v

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Question

Which measurement is more highly influenced by extreme values, the arithmetic mean or geometric mean?

Answer

Arithmetic

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r measure of the compound growth rate of an investment. When returns are variable by period, the geometric mean will always be less than the arithmetic mean. The more dispersed the rates of returns, the greater the difference between the two. <span>This measurement is not as highly influenced by extreme values as the arithmetic mean. Weighted Mean The weighted mean is computed by weighting each observed value according to its importance. In contrast, the arithmetic mean assigns equal weight

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Question

The **[...]** is computed by weighting each observed value according to its importance.

Answer

weighted mean

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less than the arithmetic mean. The more dispersed the rates of returns, the greater the difference between the two. This measurement is not as highly influenced by extreme values as the arithmetic mean. Weighted Mean <span>The weighted mean is computed by weighting each observed value according to its importance. In contrast, the arithmetic mean assigns equal weight to each value. Notice that the return of a portfolio is the weighted mean of the returns of individual assets in the portfolio. The

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Question

the return of a portfolio is the **[...]** of the returns of individual assets in the portfolio.

Answer

weighted mean

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alues as the arithmetic mean. Weighted Mean The weighted mean is computed by weighting each observed value according to its importance. In contrast, the arithmetic mean assigns equal weight to each value. Notice that <span>the return of a portfolio is the weighted mean of the returns of individual assets in the portfolio. The assets are weighted on their market values relative to the market value of the portfolio. When we take a weighted average of forward-looking data, the weighted mean is called expect

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Question

When we take a weighted average of forward-looking data, the weighted mean is called **[...]**

Answer

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assigns equal weight to each value. Notice that the return of a portfolio is the weighted mean of the returns of individual assets in the portfolio. The assets are weighted on their market values relative to the market value of the portfolio. <span>When we take a weighted average of forward-looking data, the weighted mean is called expected value. Example A year ago, a certain share had a price of $6. Six months ago, the same share had a price of $6.20. The share is now trading at $7.50. Because the most

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Question

The median is the value that **[...]**

Answer

stands in the middle of the data set, and divides it into two equal halves

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ice inflates the weighted mean relative to the un-weighted mean. Median In English, the word "mediate" means to go between or to stand in the middle of two groups, in order to act as a referee, so to speak. <span>The median does the same thing; it is the value that stands in the middle of the data set, and divides it into two equal halves, with an equal number of data values in each half. To determine the median, arrange the data from highest to lowest (or lowest to highest) and find the middle observation.

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Question

To determine the median the first step is to **[...]**

Answer

arrange the data from highest to lowest (or lowest to highest)

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groups, in order to act as a referee, so to speak. The median does the same thing; it is the value that stands in the middle of the data set, and divides it into two equal halves, with an equal number of data values in each half. <span>To determine the median, arrange the data from highest to lowest (or lowest to highest) and find the middle observation. If there are an odd number of observations in the data set, the median is the middle observation (n + 1)/2 of the data set. If the number of observation

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Question

Second step in finding the median

Answer

find the middle observation.

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value that stands in the middle of the data set, and divides it into two equal halves, with an equal number of data values in each half. To determine the median, arrange the data from highest to lowest (or lowest to highest) and <span>find the middle observation. If there are an odd number of observations in the data set, the median is the middle observation (n + 1)/2 of the data set. If the number of observations is even, there is no single mid