When writing your results, you’re going to write the decision regarding the null, but you also want to state the results in layman’s terms. Tie the statistical results back to the original claim and interpret what those statistics mean, without all the quantitative jargon.

__Examples:__

1) **Claim**: Females run faster than males.

*Results of the test*: t_{o} > t_{c}

*Decision*: Reject Null Hypothesis.

*Conclusion*: There is sufficient evidence to suggest that females run faster than males.

2) **Claim**: There is a difference in the highest level of education obtained based on socioeconomic status.

*Results of the test*: p > α

*Decision*: Fail to Reject Null Hypothesis.

*Conclusion*: There is not enough evidence to suggest that highest level of education differs based on socioeconomic status.

3) **Claim**: The number of calories consumed and the number of hours spent exercising each week are significant predictors of weight.

*Results of the test*: p < α

*Decision*: Reject Null Hypothesis.

*Conclusion*: The results of the hypothesis test suggest that a person’s weight can be predicted given caloric intake and the number of hours spent exercising each week.