Hypothesis testing comprises of a collection of data by a researcher from a population and evaluating it ( Schönbrodt et al., 2017). The study is interested in examining the body mass index of 100 individuals who visited a doctor battling with diabetes. It will establish if the body mass index (BMI) of people with diabetes is greater than 70 kgs . The result will help the clinicians and doctors to advise patient s on how body mass index affect s glucose levels .
To evaluation of the data, the study first formulat ed the hypothesis of the research , w here the null and alternative hypothes e s are stated. Then, the we determine d the best statistical test to employ in testing the hypothesis. The study will hypothesize that the individual body mass index (BMI) will be greater than 70 kgs . Given that from a sample of 100 patients the mean BMI is 65 kgs with a standard deviation of 10 kgs, the null and alternative hypothes es are formulated as follows :
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H0: The body mass index is equal to 70 kg (
H1: The body mass index is greater than 70 kg ( .
This is a one tail test with a significance level, alpha = 0.05.
We use the following statistic,
Z =
= = 5
= = 5
The computed value is 5
Using the Z normal tables, we find the tabulated value given alpha = 0.05
Tabulated Z value = 1.96
We compared the computed and tabulated values. Since the computed value is greater, when compared with the tabulated value, we reject the null hypothesis, Zc = 5 > Zt = 1.96 . Therefore, we deduce that the body mass index is significantly greater than 70 kgs.
Reference
Schönbrodt, F. D., Wagenmakers, E. J., Zehetleitner, M., & Perugini, M. (2017). Sequential hypothesis testing with Bayes factors: Efficiently testing mean differences. Psychological methods , 22 (2), 322.
