Data Analysis - Descriptive Stats Flashcards

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1
Q

Define descriptive statistics.

A

Involve summarising sets of quantitative data.

Present findings from your research in a clear and condensed form.

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2
Q

What do descriptive stats include?

A
  1. Measures of central tendency.
  2. Measures of dispersion.
  3. Data tables.
  4. Graphs and charts.
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3
Q

Define measures of central tendency.

A

They are averages.

They provide a single value which is representative of a whole set of scores by indicating the more typical value.

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4
Q

What are the 3 measures of central tendency?

A

Mode, Median, Mean.

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5
Q

What is the mode?

A

The most frequently occurring value.

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6
Q

What is the median?

A

The middle value when the scores are arranged from biggest to smallest/ smallest to biggest ( ascending/ descending).

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7
Q

How do you work out the median?

A

When there is an even number of scores in a set the 2 middle values are added together and divided by 2.

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8
Q

What is the mean?

A

The arithmetic average.

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9
Q

How do you work out the mean?

A

Adding up all of the scores in the set and dividing by the total number of scores in the set.

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10
Q

What are some advantages of mode?

A

It represents a figure that does actually occut in a set of data.
Unaffected by one or two extreme scores.

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11
Q

Whatvare some disadvantages of mode?

A

Does not tell us anything about the other values in a set of data.
Small changes in the data can radically alter the mode.

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12
Q

What are some advantages of median?

A

It remains relatively unaffected by any outlying (extreme) values.
It can be used in data with skewed distributions.

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13
Q

What are some disadvantages of median?

A

It doesn’t work well with small sets of data.

Is affected by any alteration of the central values in a set of values.

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14
Q

What are some advantages of mean?

A

Makes use of all the data in a set.

Is therefore the most powerful measure of central tendency.

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15
Q

What are some disadvantages of mean?

A

It shouldn’t he used on skewed data that has one or two outlying values - this can give a misleading average.
Inappropriate to use on ordinal and nominal data.

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16
Q

What are measures of dispersion?

A

They measure how spread out the scores are within a set of data.

17
Q

What do large/ small measures of dispersion show?

A

A large meausre of dispertion shows that the scores are widely scattered.
A small measure of dispertion shows that the scores are closely clustered.

18
Q

What are the 3 measures od dispertion?

A

Range, Interquartile range, Standard deviation.

19
Q

What is the range?

A

The difference between the highest and the lowest scores in a set of data.

20
Q

How do you work out the range?

A

Subtract the lowest value from the highest value.

21
Q

What is the interquartile range?

A

Measures the spread of scores in the middle 50% of values when they are places in numerical order.

22
Q

What is standard deviation?

A

Measures the average distance of rach score away from the mean.

23
Q

What are some advantages of range?

A

Easy to calculate

24
Q

What are some disadvantages of range?

A

Only considers the two extreme values in its calculation.

It doesnt tell us anything about the distribution of the scores in the middle of the set.

25
Q

What are some advantages of interquartile range?

A

The top & bottom 25% are ignored which gets over the problem of outlying values.

26
Q

How do you calculate the interquartile range?

A

Calculate the median.
Calculate the mean of the 25% that is the closest above the median and the same for below the median.
The interquartile range is the difference between the mean values of upper and lower boundries.

27
Q

What are some advantages of standard deviation?

A

The most powerful measure of dispertion, as it uses all the scores in the set of data in the calculation.
It can be used to describe the spead of scores in a normal distribution.

28
Q

What are some disadvantages of standard deviation?

A

It is less effective when there are outlying scores that skew data.