Descriptive Statistics

Question 1

Collapsing data

Answer 1

Take large data set and condense it into what you need.

Question 2

Central Tendency Measures

Answer 2

• Mean
• Median
• Mode

Question 3

Variability

Answer 3

Spread in the data

Question 4

Distribution =

Answer 4

total set of scores (n)

Question 5

Frequency distribution

Answer 5

• Rank that shows the number of times each value occured or frequency

Allows to examine the distribution of scores

Question 6

Ideal frequency distribution shape is a

Answer 6

bell curve

Question 7

Cummulative Percentage

Answer 7

% of people that fall below a score

Question 8

What are 4 ways to describe the distribution of the shapes of graphs?

Answer 8

• Symmetrical
• Uniform
• Normal
• Skewed (doesn’t follow normal curve)

Question 9

Positive vs Negative Skewed Bell Curve

Answer 9

• Negative skew: tail goes out toward negative side
• Positive skew: tail goes out toward positive side

Question 10

Mode

Answer 10

• Most frequent number
• Not useful for continuous data
• bimodal = 2; multimodal = greater than 2

Question 11

Median

Answer 11

• Middle Score

Advantage:
* Unaffected by extreme scores
* Average position in the distribution, not amount
* Useful for skewed data with extreme scores

Question 12

Mean

Answer 12

• Average

Sum of scores/n

Question 13

Most appropriate type of type of measurement and central tendency

Answer 13

• Interval/Ratio = Mean
• Ordinal = median or mode
• Nominal = Mode
• Mean is the most stable measure but is largely affected by skew
• Median/Mode are less affected by skew

Question 14

Measures of variability

Answer 14

• Variability = dispersion of scores

Measures of variability:
* Range (max - min)
* Percentiles and quartiles
* Variance (spread)
* Standard Deviation
* Coefficent of variation

Question 15

Range

Answer 15

• Range = maximum - minimum)
• Least useful
• Greatly affected by outliers
• Hard to compare different sample sizes

Question 16

Percentile definition

Answer 16

• relative position within a distribution based on 100 equal portions

Question 17

Quartiles

Answer 17

• Distribution split into 4 equal parts
• Often use quartiles to divide samples into subgroups
• Ex: compared those below 1st. (“lax”) vs. those above the 3rd. (“tight”) - two different groups.

Question 18

Variance

Answer 18

• Index that effects the spread in scores
• The bigger the number the bigger the variance
• Not normal units

Question 19

Standard Deviation

Answer 19

• Brings variability back to normal units
• Often seen as either: 38.6±3.2° or 38.6° (sd 3.2°)

Question 20

Most biological, psycholigcal and social phenomena fall into a normal curve. What things do not?

Answer 20

income, socioeconomic class, politcs

Question 21

Proportions of the Normal Curve

Answer 21

• Bell Curve
• Scores clusters around mean
• Mean, median, mode are the same
• Frequency changes as you get away from mean

Question 22

SD and Percentages

Answer 22

1 SD = 68%
2 SD = 95%
3 SD = 99%

Question 23

Outliers

Answer 23

• Outlier = an observation whose value is distant from the values of the majority of observations
• Influence skewness and move mean in direction of the outlier

Question 24

Box and Whisker Plot

Answer 24

• Interquartile Range: 25%-Median-75%
• Outliers lie outside of the plot

Question 25

Effect Size

Answer 25

• Calculated to determine the “meaningful” change
• Cohen’s d is often used to examine effect size

Question 26

Cohen’s d

Answer 26

ES = Change in Score/Average Standard Deviation

Question 27

Effect Size Interpretation

Answer 27

• Greater than 0.8 = large = meaningful
• Less than 0.8 = not meaningful