# What is your research question? Is there a difference between the math utility of a male and a female? What is the null hypothesis for your question?

- What is your research question?

Is there a difference between the math utility of a male and a female?

- What is the null hypothesis for your question?

H_{n }There is no difference in the math utility between male and female.

Alternative hypotheses can also be created in the case the null hypothesis is proven incorrect. Two alternative hypotheses are:

H_{a1 }Feales have a higher math utility.

H_{a2 }Males have a higher math utility.

- What research design would align with this question?

According to Frankfort-Nachmias and Leon-Guerrero (2015) a descriptive research design would be best for this type of study.

- What comparison of means test was used to answer the question (be sure to defend the use of the test using the article you found in your search)?

The independent-samples T test was used to analyze the means for this data.

- What dependent variable was used and how is it measured?

The dependent variable is the student’s math utility. It is measured from -3.51 to 1.31(University high school longitudinal study dataset. (2009).

- What independent variable is used and how is it measured?

Either male (1) of female (2) (University high school longitudinal study dataset. (2009).

- If you found significance, what is the strength of the effect?

The significance was 0.0000. This is much better than the standard of .05 significance as outlined by Frankfort-Nachmias and Leon-Guerrero (2015).

- Identify your research question and explain your results for a lay audience, what is the answer to your research question?

My research question was “Is there a difference between the math utility of a male and a female?” Based on the analysis of the means (or average) through testing using the independent-samples T test there was no measurable difference between the math utility of male or females. This leads us to accept the null hypothesis of “There is no difference in the math utility between male and female” as true.

Group Statistics |
|||||

T1 Student’s sex | N | Mean | Std. Deviation | Std. Error Mean | |

T1 Scale of student’s mathematics utility | Male | 9453 | .0140 | 1.01962 | .01049 |

Female | 9349 | -.0481 | .97291 | .01006 |

Independent Samples Test |
||||||||||

Levene’s Test for Equality of Variances | t-test for Equality of Means | |||||||||

F | Sig. | t | df | Sig. (2-tailed) | Mean Difference | Std. Error Difference | 95% Confidence Interval of the Difference | |||

Lower | Upper | |||||||||

T1 Scale of student’s mathematics utility | Equal variances assumed | 17.400 | .000 | 4.276 | 18800 | .000 | .06216 | .01454 | .03367 | .09066 |

Equal variances not assumed | 4.277 | 18775.932 | .000 | .06216 | .01453 | .03367 | .09065 |

University high school longitudinal study dataset. (2009).

References

Frankfort-Nachmias, C., & Leon-Guerrero, A. (2015). *Social statistics for a diverse society* (7th ed.). Thousand Oaks, CA: Sage Publications.

University high school longitudinal study dataset. (2009). Retrieved from class.waldenu.edu