Inferential statistics end of topic quiz

What is the main purpose of Spearman's rank order correlation coefficient?

• To see if the correlation between co-variables is significant or not.

• To calculate the mean of a data set.

• To determine the mode of a distribution.

• To find the standard deviation of a sample.

Which correlation coefficient did Diener et al. (1993) find between happiness and money?

• +0.12

• +1.00

• -0.50

• 0.00

Who is associated with the development of the rank order correlation coefficient discussed in the material?

• Charles Spearman

• Sigmund Freud

• Ivan Pavlov

• Jean Piaget

What is the minimum level of measurement required for data to use Spearman's rank order correlation coefficient?

• At least ordinal

• Nominal

• Ratio only

• Interval only

What type of data does the Chi-Square (χ²) test deal with?

• Nominal data

• Interval data

• Ratio data

• Ordinal data

When should you use the Chi-Square (χ²) test?

• When you have counted how many occurrences there are in each category (frequency data)

• When you are measuring the average of a continuous variable

• When you are comparing means between two groups

• When you are analyzing time series data

Which of the following is a requirement for using the Chi-Square (χ²) test?

• Data must be in frequencies (nominal) and not in percentages

• Data must be in percentages

• Data must be continuous

• Data must be ordinal

When are tests of difference generally used?

• For experiments

• For surveys only

• For descriptive statistics

• For measuring central tendency

Who is the Wilcoxon Matched Pairs Signed Ranks Test named after?

• Frank Wilcoxon

• Albert Einstein

• Ronald Fisher

• Charles Darwin

When should you use the Mann-Whitney U test?

• When the hypothesis predicts a difference between two sets of data, the data comes from independent groups, and the data is not nominal.

• When the hypothesis predicts a relationship between variables, and the data is nominal.

• When the data is from the same group measured twice.

• When the data is always nominal.