EIP - Summarising Data - Week 4 Flashcards

1
Q

Name and describe the two types of data. Give some general examples.

A

Qualitative - individuals can be divided into separate classes like gender, hair colour, eye colour.
Quantitative - numerical like number of students, height, weight

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2
Q

List the two types of qualitative data.

A

Nominal - unordered like gender, hair colour

Ordinal - ordered - severity rating

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3
Q

Define frequency.

A

The count of individuals with a particular quality

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4
Q

What is the cumulative frequency of a value and what two types of data is it used for?

A

The number of subjects with values less than or equal to that value
Used only for ordinal qualitative variables or quantitative variables

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5
Q

Define mode.

A

Most frequent value/observation

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6
Q

In what distributions is the mode used?

A

Unimodal distributions only.

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7
Q

Define positive and negative skews in a distribution.

A

Skewed positively - to the right (median to the left)

Skewed negatively - to the left (median to the right)

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8
Q

What does the interquartile range give a measure of?

A

Statistical variability or spread

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9
Q

What is the formula for the max and min values on a box and whisker plot?

A
Max = Q3 + 1.5 x IQR
Min = Q1 - 1.5 x IQR
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10
Q

What is the mean commonly used to illustrate?

A

Central tendency

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11
Q

What is range often used to illustrate?

A

Dispersion/spread/viability of the entire dataset

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12
Q

What is the interquartile range used to illustrate?

A

The spread of the central 50% of the data

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13
Q

What is the variance used to illustrate?

A

Spread of the data

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14
Q

What is variance?

A

Sum of the squared deviations from the mean, divided by degrees of freedom (sample size minus one)

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15
Q

What is standard deviation?/

A

Square root of the variance

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16
Q

Define the following standard deviations in a normal distribution: 1, 2, and 3.

A

1 - 68%
2 - 95%
3 - 99.7%

17
Q

What is standard error of the mean and what value does it have when the sample size is large?

A

Standard deviation divided by the square root of the sample size
When sample size is large, SEM is small

18
Q

What is the standard error of the mean used to estimate? Why does it decrease with increasing sample size?

A

Used to estimate confidence limits for a mean.

When the sample size is very large, the SEM would become small since the sample mean would approach the population mean.