Question

Employers, the military, and colleges use aptitude tests to predict how well someone might perform. Recently, critics have said that everyone is more or less the same above a certain level—there isn’t much difference in performance. Now, in the current issue of Psychological Science, the authors of a new study found that this isn’t true. Instead, the higher your score, the better you perform later. The investigation considered four large studies of people who have taken aptitude tests: the College Board’s SAT scores for 150,000 students entering 110 colleges and their freshman GPA. The army collected 5,000 scores for the Armed Services Vocational Aptitude Battery and later appraised candidates on how well they did their jobs. Two additional data sets contained students’ performance on tests in high school and their grades in college. The higher the test scores, the better the subsequent performance.

-What, according to you, could be an alternative hypothesis that could equally explain this finding? Which one would you choose? Explain your choice.

-When you reply to your classmates’ posts, respectfully agree/disagree to the post and explain why, while offering an opinion with an example to support it.

Answer 1

Answer :

Inference about the population parameter is a statistical hypothesis. This statement may be accurate or not. Hypothesis testing means the systematic methods used in approving or rejecting statistical theories used by statisticians.

A sample of the whole population will be the best way to determine whether a statistical hypothesis is valid. As this is often unworkable, researchers usually test a random population sample. If the experimental data do not fit the statistical hypothesis, the hypothesis will be rejected.

The statistical hypotheses are two forms.

• Null hypothesis: The null hypothesis, referred to by Ho, is typically a hypothesis which results in pure chance observations.

• Alternative hypothesis:  It is referred to as H1 or Ha and is hypothesized that some non-random cause affects sample observations.

The concept of null hypothesis and alternative hypothesis will be clear from the illustrations stated below:

Example: Two additional data sets included students’ performance on tests in high school and their grades in college. Different institutes conduct aptitude tests to predict the performance of the people. The performance is based on the scores a person obtains.

As given in case:

Null hypothesis: H ₀: higher scores of the test indicate a better performance

Alternative hypothesis: H ₁: higher scores of the test do not indicate a better performance

The statistical studies reveal that high scores of a person in an aptitude test ensure better performance. Hence, the null hypothesis cannot be rejected here.

This demonstrates that statistical tests are correct. A higher score in the aptitude tests indicates a better performance, presented all the other factors remain fixed.

I am agreed with the classmate's post,as it is statistically proven that  The higher the test scores, the better the subsequent performance.

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