Question

Data set used for females and males on ADHD medications. Explain this data for a research paper doing a t-test. The hypothesis is that gender plays a role in youth being put on medications---more males are put on medications than females. Females: 33, 29, 35, 39, 39, 41, 25, 33, 38 Males: 46, 43, 42, 46, 44, 47, 50, 43, 39

I received the statistical computation for this data set. How can this be explained in words for a research paper? Thank you

Answer 1

First of all, write down the null hypothesis and alternate hypothesis

Null hypothesis :- there is no difference between means of male and female groups

Alternate hypothesis:- mean for male group is significantly higher than mean for female group

I dont know what your statistical computation tells about the final result, so i will provide both scenarios

SCENARIO 1

when the p value corresponding to test statistic is less than significance level 0.05, then we reject the null hypothesis in this case because the result is significant

Write result in APA format as follows

t(df,alpha level) = ..... with p value = .....

(write down your test statistic and p value)

df is degree of freedom = n1+n2-2 = 9+9-2 = 16 and alpha level is significance level, like 0.05

Conclusion:- since the p value is less than significance level and we rejected the null hypothesis. Therefore, we can say that there is sufficient evidence to conclude that mor males are put on medications than females

SCENARIO 2

when the p value corresponding to test statistic is more than or equal to significance level 0.05, then we failed to reject the null hypothesis in this case because the result is insignificant

Write result in APA format as follows

t(df,alpha level) = ..... with p value = .....

(write down your test statistic and p value)

df is degree of freedom = n1+n2-2 = 9+9-2 = 16 and alpha level is significance level, like 0.05

Conclusion:- since the p value is more than significance level and we failed to reject the null hypothesis. Therefore, we can say that there is insufficient evidence to conclude that mor males are put on medications than females