A hairdresser wanted to see if her clients bought more products at the end of their appointment if they were given lots of compliments. She decided to test this theory using an experiment. She randomly assigned 24 clients to receive either zero compliments, 5 compliments, or 10 compliments during their appointment. She recorded how many products they purchased after their appointment as her DV. She firstly hypothesised that no-compliment clients (M = 0.38) would purchase fewer products than clients who received 5 compliments (M = 1.50). She secondly hypothesised that 5-compliment clients would purchase fewer products than 10-compliment clients (M = 3.63). Thus, she conducted two comparisons. The initial ANOVA was significant. Using an alpha of .05, results for the follow-up tests confirmed her first hypothesis, with an obtained t value of 2.60, but did not confirm her second hypothesis, with an obtained t value of 1.20. She later realised that she did not use a Bonferroni-corrected critical value to assess her obtained t statistics against. If she re-did the t tests with the corrected critical value, would this have changed her conclusions?     Conclusions for both hypotheses would stay the same     Conclusions for both hypotheses would change     Conclusions for Hypothesis 1 would change, and conclusions for Hypothesis 2 would stay the same     Conclusions for Hypothesis 1 would stay the same, and conclusions for Hypothesis 2 would change

A hairdresser wanted to see if her clients bought more products at the end of their appointment if they were given lots of compliments. She decided to test this theory using an experiment. She randomly assigned 24 clients to receive either zero compliments, 5 compliments, or 10 compliments during their appointment. She recorded how many products they purchased after their appointment as her DV.

She firstly hypothesised that no-compliment clients (M = 0.38) would purchase fewer products than clients who received 5 compliments (M = 1.50). She secondly hypothesised that 5-compliment clients would purchase fewer products than 10-compliment clients (M = 3.63). Thus, she conducted two comparisons.

The initial ANOVA was significant. Using an alpha of .05, results for the follow-up tests confirmed her first hypothesis, with an obtained t value of 2.60, but did not confirm her second hypothesis, with an obtained t value of 1.20.

She later realised that she did not use a Bonferroni-corrected critical value to assess her obtained t statistics against. If she re-did the t tests with the corrected critical value, would this have changed her conclusions?