√Z/N

Z/√N

Z/N

√Z/√N

The effect size

The standard deviation

The variance

The mean

the z value

the p value

df

The medians

df

t statistic

p value

number of participants

Mode

Median

Mean

Wilcoxen matched pairs

Independent t test

Chi-squared

(c-1)x(r-1)

(columns x rows) - 1

(c+1)x(r+1) -1

(c-1)+(c-1) -1

(columns + rows) - 1

The standard deviation = 1

The mean = 0

The mean = 1

The standard deviation = 0

X - mean/ standard deviation

X + standard deviation/ mean

mean - standard deviation/ X

mean - X/ standard deviation

Represents the percentage of participants

Equals 1

None of these are correct

Equals 100

0.5

0.1

0.3

0.8

determines the likelihood that the variance in two samples is roughly equal

determines the likelihood that two groups come from the same population

determines the likelihood that the results are significant

determines the likelihood of the data belonging to a normal distribution

determines the likelihood that the data comes from one sample

Data where the results of Levene's and the K-S test are not significant

Memory scores recorded before and after memory training that are normally distributed and variances of the two groups are roughly equal

Scores on a questionnaire that are normally distributed

Data recording whether a person passes or fails a false belief task

determines the likelihood that the variance of two or more samples are roughly equal

determines the likelihood that the mean of a sample is significantly different to chance

determines the likelihood that a sample is normally distributed

determines the likelihood that a sample is skewed

determines the likelihood that the variance of a sample is very large

Is tested for using Levene's test

The assumption that the variance in multiple samples are roughly equal

Is tested for using the Kolmogorov-Smirnov test

An important assumption of parametric tests

The assumption that the variance in a sample is skewed

The assumption that the variance in a sample is very small