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

Question

Examples **[...]** data would include the height of a person and the time to complete an assignment.

Answer

Continuous

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

Question

Examples **[...]** data would include the height of a person and the time to complete an assignment.

Answer

?

Tags

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

Question

Examples **[...]** data would include the height of a person and the time to complete an assignment.

Answer

Continuous

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an>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.<span><body><html>

#### Original toplevel document

**Subject 3. Frequency Distributions**

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

an>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.<span><body><html>

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

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 |

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