Descriptive Statistics

Question 1

Measures of central tendency

Answer 1

Denote the average, most frequent score (mean, median, mode)

Question 2

Mode

Answer 2

The value occurring most often in a data set. Nominal data.

Distribution: mode sits as highest point in the curve

Question 3

Median

Answer 3

Middle value of the data set; divides the distribution in half.
To calculate, order all responses, response in the exact middle of the data set is median.
Ordinal data (or other quantitative data)
Distribution: center value in set, regardless of curve

Question 4

Mean

Answer 4

Mathematical middle of the data set
Sum of all responses divided by n- number of responses
Interval and ratio data
Distribution depends on range and skew of data- it is the most sensitive to change as it mathematically considers every score
Not appropriate to use when there are outliers because it is such a sensitive measure

Question 5

What does it mean if mean, median, and mode are all the same?

Answer 5

symmetrical distribution

Question 6

What does it mean if mean, median, and mode are different?

Answer 6

There will be skew.

Question 7

When would median be a better indicator of central tendency than mean?

Answer 7

If skew is severe enough. And you may want to consider avoiding parametric stats

Question 8

How many decimal places do you round to when calculating mean, median and mode?

Answer 8

Two

Question 9

What type of data is best described by mode?

Answer 9

nominal

Question 10

What type of data is best described by median?

Answer 10

ordinal, interval skewed and ratio skewed

Question 11

What type of data is best described by mean?

Answer 11

interval normal and ratio normal

Question 12

What happens to variance when you add more participants to your sample?

Answer 12

It mimics the population more

Question 13

What are sources of variance?

Answer 13

• Participants/people
• Environment
• Measurement

Question 14

What type of variance is error?

Answer 14

• Measurement

- Researcher

Question 15

What are some measures of variability?

Answer 15

• range
• standard deviation
• variance

Question 16

Range

Answer 16

• The simplest measure of variability
• defined by the lowest and highest values in the data set (subtract lowest from highest and the different is range)
• more common to actually report low and high values

Question 17

Standard deviation

Answer 17

We figure out how much individual scores vary from the mean, then calculate what was the standard amount of variance from the mean. Take individual variance (each person’s deviation from the mean) and combine it to form a group variance.

Question 18

What additional information do measures of variance give us beyond what measures of central tendency do?

Answer 18

Range and the standard amount of variation within the sample

Question 19

Random error

Answer 19

occurs through random selection/assignment:

• characteristics don’t mimic population
• one group different than other before you start
• this is why some researchers use other types of sampling/assignment than true random

Question 20

Systematic error

Answer 20

Mistake made on a repeated basis that affects accuracy (ex: clock consistently 5 min fast)

Question 21

Errors of Omission

Answer 21

Individual collecting data does something wrong with or without realizing they’ve done something wrong (ie misread directions)

Question 22

Errors of Commission

Answer 22

Individual knows better and still deviates from what they should:

• only use partial results
• uses a subtest that is not appropriate for a subgroup included in sample

Question 23

Sources of Error

Answer 23

• Researcher
• Participants
• Measurement
• Environment

Question 24

What effect does error have on power?

Answer 24

It reduces it.

Question 25

What are skew and representational error often signs of?

Answer 25

Variance not found in population. One way to decrease skew and representational error is to increase your sample.

Question 26

How is sample size related to power?

Answer 26

Power is a function of sample size:

more participants=less error; less error=more power; more participants=more power

Question 27

What are ways to plan a powerful study?

Answer 27

• select an adequate sample size

- control for threats to research

Question 28

Type I error

Answer 28

a false rejection of the null hypothesis (false positive)

related to our inferences: null hypothesis v. research hypothesis

Question 29

Type II error

Answer 29

accepting the null hypothesis of no difference when it is not true (false negative)
related to our inferences: null hypothesis v. research hypothesis

Question 30

What factors determine power?

Answer 30

effect size, the sample size, the alpha level, and the chosen power that you want (typically 80%)