Statistical tests

• Statistical tests= Used in psychology to determine whether a significant difference or correlation exists, and if the null hypothesis should be rejected or retained.
• Sign test= A statistical test for a difference in scores between related items. Data should be nominal level or better.
• Levels of measurement= Quantitative data can be classified into types or levels of measurement, such as nominal, ordinal and interval.
• Spearman’s rho= A test for correlation when data is at least ordinal level.
• Pearson’s r= A parametric test for correlation when data is at an interval level.
• Wilcoxon= A test for difference between two sets of scores. Data should be at least ordinal level using a repeated measures design.
• Mann-Whitney= A test for a difference between two sets of scores. Data should be at least ordinal level using independent groups.
• Related t-test= A parametric test for a difference between two sets of scores, data must be interval level with a repeated design e.g. repeated measures.
• Unrelated t-test= A parametric test for the difference between two sets of scores, data must be interval level with an unrelated design e.g. independent groups.
• Chi-squared= A test for association between two variables or conditions, data should be nominal level using an unrelated design.
• Decision 1: Difference or correlation

  • First thing to think about when choosing a statistical test is what is the aim/purpose of the investigation.
  • Is the researcher looking for a difference or correlation.
• Decision 2: Experimental design

  • Is it unrelated or related.
  • E.g. repeated measures and matched pairs are related.
  • E.g. independent groups are unrelated.
• Decision 3: Levels of measurement

  • Which type of data does the researcher have.
  • Nominal, ordinal or interval.
• Nominal data= Data is represented in the form of categories. E.g. you can count haw many girls and boys are in the classroom, there is two categories, female and male and take note of how many are in each category. This data is discrete, one item can only appear in one of the categories.
• Ordinal data= Data is ordered in some way. E.g. everyone would rate how ugh they enjoyed maths on a scale of 1-10. There is no equal intervals in ordinal data because if someone chooses 8 it doesn’t mean they enjoy maths twice as much as someone who choose 4. It lacks precision as its subjective.
• Interval data= Based on numerical scales that include units of equal defined size. E.g. stopwatch or weighing scales. Most precise.
• Nominal data:

  • Measure of central tendency- Mode
  • Measure of dispersion- N/A
• Ordinal data:

  • Measure of central tendency- Median
  • Measure of dispersion- Range
• Interval data:

  • Measure of central tendency- Mean
  • Measure of dispersion- Standard deviation
• Sentence to remember test table-

  Can Sophie Chew Mushrooms When She’s Under Rushed Pressure.