You need to conduct a hypothesis test about two population means. Since the t-test for two population means compares the means for two populations, your dataset should contain a binary (dummy/indicator) variable that divides your sample into two groups (e.g. female vs. male, developing countries versus developed countries). If the variable is not a binary variable, you may create one based on other variables. For example, using the variable “age”, you can generate a binary variable called “senior” by coding individuals with age older than 64 as senior people, if your research question is to examine whether there exists a difference between senior's income and non-senior's income.
Your dataset should also contain another interval or ratio variable, for which you want to
compare the means. A nominal variable, unless it is dummy (binary) variable, generally would not be used, as a dependent variable. In your report, you need to state the research question you try to answer, your null hypothesis and alternative hypothesis. You should also briefly explain why the question is of your interest. Next, you should discuss whether you will use a paired-sample t-test or a t-test for two independent means. And explain why this particular test method, instead of the alternative, is chosen. Then you should present your test results in a table and interpret them in the text, followed by a conclusion on whether the analysis supports or rejects your null hypothesis. Please also explain whether the conclusion is line with your expectation, what the theory predicts or what the literature has found. If it is not, please provide some plausible explanations.
The question belongs to Statistics and it discusses about analyzing the data for statistical difference in the weight of male and female babies.
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