Stats

Question 1

One sample, parametric data

Answer 1

One sample t test

Question 2

Two samples, parametric data

Answer 2

Two sample t test

Question 3

Two related samples, parametric data

Answer 3

Paired sample t test

Question 4

Three + samples, parametric data

Answer 4

One-way ANOVA

Question 5

Relational, parametric data

Answer 5

Pearson correlation coefficient or simple linear regression

Question 6

Explanatory, parametric data

Answer 6

Multiple Regression

Question 7

One sample, non-parametric data

Answer 7

Chi square

Question 8

Two samples, non-parametric data

Answer 8

Chi-square (for nominal and ordinal). Mann-Whitney (for ordinal, interval and ratio data).

Question 9

Two related samples, non-parametric data

Answer 9

Friedman test. Wilcoxon test (for ordinal, interval and ratio data.)

Question 10

Three + samples, non-parametric data

Answer 10

Chi-Square (for nominal and ordinal data). Kruskal-Wallis (for ordinal, interval and ratio data).

Question 11

Relational, non-parametric data

Answer 11

Spearman rank correlation coefficient. Logistic regression.

Question 12

Explanatory, non-parametric data

Answer 12

Multiple logistic regression.

Question 13

Normal distribution, known as

Answer 13

Gaussian distribution

Question 14

Parametric data is data

Answer 14

that are measure on interval/ratio scales and data that are not normally distributed.

Question 15

Non-parametric data is data

Answer 15

Nominal/ordinal data or interval/ratio data that are not normally distributed.

Question 16

Test for normal distribution

Answer 16

Kolmogorov-Smirnov test.

Question 17

Devon vs UK incomes

Answer 17

One sample t

Question 18

Devon vs Dorset incomes

Answer 18

Two sample t test

Question 19

Devon incomes 2000 vs Devon incomes 2002

Answer 19

Paired sample t test

Question 20

Devon vs Dorset vs Somerset incomes

Answer 20

One-way ANOVA.

Question 21

Income correlated with spending on holidays

Answer 21

Pearson correlation coefficient or simple linear regression

Question 22

Income and age predicting holiday spending

Answer 22

Multiple regression

Question 23

Devon sites vs UK sites visited

Answer 23

Chi-square

Question 24

Devon vs Dorset sites visited

Answer 24

Chi-Square (for nominal and ordinal data). Kruskal-Wallis (for ordinal, interval and ratio data).

Question 25

Devon sites visited 2000 and 2001

Answer 25

Friedman test. Wilcoxon test (for ordinal, interval and ratio data.)

Question 26

Devon vs Dorset vs Somerset sites visited

Answer 26

Chi-Square (for nominal and ordinal data). Kruskal-Wallis (for ordinal, interval and ratio data).

Question 27

Income correlated with number of sites visited

Answer 27

Spearman rank correlation coefficient. Logistic regression.

Question 28

Income and age predicting sites visited.

Answer 28

Multiple logistic regression.

Question 29

Nominal Data

Answer 29

Refers to categorically discrete data such as name of your school, type of car you drive or name of a book

Question 30

Ordinal Data

Answer 30

Refers to quantities that have a natural ordering. The ranking of favorite sports, the order of people’s place in a line, the order of runners finishing a race or more often the choice on a rating scale from 1 to 5.

Question 31

Interval data

Answer 31

Is like ordinal except we can say the intervals between each value are equally split. The most common example is temperature in degrees Fahrenheit.

Question 32

Ratio data

Answer 32

is interval data with a natural zero point. For example, time is ratio since 0 time is meaningful. Degrees Kelvin has a 0 point (absolute 0) and the steps in both these scales have the same degree of magnitude.

Question 33

Discontiuous/discrete data

Answer 33

Whole number values, such as the number of students attending a course. Nominal and ordinal data often reflects discrete data

Question 34

Continuous variables

Answer 34

These are variables which have an infinite number of fractional points e.g. height

Question 35

Categorical data

Answer 35

Data subdivided in categories. Nominal data is subdivided in unordered categories, while categories of ordinal data have an internal order.

Question 36

R squared

Answer 36

the ‘goodness of fit’ that the model offers, expressed in per cent.

Question 37

B

Answer 37

The regression Coefficient

Question 38

t

Answer 38

The ‘significance’ of the coefficient in explaining the variance.

Question 39

F

Answer 39

The significance of the overall model in explaining the variance.

Question 40

Equation for a straight line

Answer 40

y= a + bx

Question 41

y =

Answer 41

dependent variable

Question 42

b =

Answer 42

slope gradient

Question 43

a =

Answer 43

intercept

Question 44

x =

Answer 44

independent variable