Q: What does p<0.05 mean in psychology research?

It means there is less than a 5% probability that the observed results occurred by chance alone. In other words, if the null hypothesis were true, you would get these results fewer than 5 times out of 100. Psychologists accept this as evidence that the independent variable had a real effect. If p is greater than 0.05, the result is not significant, and we cannot reject the null hypothesis.

Q: How do I write a conclusion for a statistical test in my psychology exam?

Your conclusion should include: the calculated value (e.g., U=12), the critical value from the table (e.g., critical value=8 for p<0.05), whether the calculated value is greater or less than the critical value, and whether the result is significant. For example: 'The calculated value of U=12 is greater than the critical value of 8 at p<0.05, so the result is not significant. We accept the null hypothesis and conclude there is no significant difference between the two conditions.'

Q: What is the sign test and when do I use it?

The sign test is a non-parametric inferential test used for nominal data in a related design (e.g., repeated measures or matched pairs). It compares the direction of differences between pairs (e.g., whether scores increased or decreased). You count the number of positive and negative signs and use the binomial distribution to determine significance. It is simple but less powerful than other tests, so it's often used when data are only at the nominal level.

Question 1

How do I choose the right statistical test for my psychology experiment?

Accepted Answer

You need to consider three things: the experimental design (related or unrelated), the level of measurement (nominal, ordinal, interval), and the type of hypothesis (directional or non-directional). For example, if you have an unrelated design with ordinal data, use the Mann-Whitney U test. If you have a related design with nominal data, use the sign test. Always check the conditions in your exam board's formula sheet.

Question 2

What is the difference between a bar chart and a histogram in psychology?

Accepted Answer

A bar chart is used for categorical (nominal) data, such as the number of males vs. females in a study. The bars are separated by gaps to show distinct categories. A histogram is used for continuous (interval/ratio) data, such as reaction times grouped into intervals (e.g., 100-200ms). The bars touch each other to indicate the continuous nature of the data. In psychology, bar charts are more common for displaying means of different conditions.

Question 3

How do I calculate and interpret standard deviation for my psychology data?

Accepted Answer

Standard deviation measures how spread out scores are from the mean. To calculate it, find the mean, subtract the mean from each score, square the differences, sum them, divide by the number of scores (or n-1 for sample), and take the square root. A small standard deviation means scores cluster closely around the mean, indicating consistency. A large standard deviation means scores are more spread out, suggesting greater variability. In psychology, this helps assess the reliability of your results.

Question 4

What does p<0.05 mean in psychology research?

Accepted Answer

It means there is less than a 5% probability that the observed results occurred by chance alone. In other words, if the null hypothesis were true, you would get these results fewer than 5 times out of 100. Psychologists accept this as evidence that the independent variable had a real effect. If p is greater than 0.05, the result is not significant, and we cannot reject the null hypothesis.

Question 5

How do I write a conclusion for a statistical test in my psychology exam?

Accepted Answer

Your conclusion should include: the calculated value (e.g., U=12), the critical value from the table (e.g., critical value=8 for p<0.05), whether the calculated value is greater or less than the critical value, and whether the result is significant. For example: 'The calculated value of U=12 is greater than the critical value of 8 at p<0.05, so the result is not significant. We accept the null hypothesis and conclude there is no significant difference between the two conditions.'

Question 6

What is the sign test and when do I use it?

Accepted Answer

The sign test is a non-parametric inferential test used for nominal data in a related design (e.g., repeated measures or matched pairs). It compares the direction of differences between pairs (e.g., whether scores increased or decreased). You count the number of positive and negative signs and use the binomial distribution to determine significance. It is simple but less powerful than other tests, so it's often used when data are only at the nominal level.

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