
Learn how a working hypothesis frames research questions and tests relationships between variables, covering simple, complex, null, alternative, directional, non-directional, causal, empirical, and statistical types.
Calculate t critical values by determining degrees of freedom (sample size minus one) and alpha (5 percent), then read the intersection on the t-table for one- and two-tailed tests.
Compare parametric and non parametric tests and learn when to apply each, based on population knowledge and data scale from nominal to ratio.
Learn the p-value approach to hypothesis testing by calculating the z statistic, deriving the p-value, and deciding to reject or accept the null hypothesis based on alpha; illustrated with example.
State the null and alternative hypotheses, compute the chi-square statistic from observed and expected frequencies, and conclude the data do not follow a uniform distribution.
Learn to perform a one-way ANOVA in Excel to test differences among three players’ scores, including null and alternative hypotheses, F value versus F critical, and p-value interpretation.
Perform a one-sample t-test in Excel to assess if the population mean exceeds 20, using a one-tailed test with alpha 0.05, interpreting the t-statistic and p-value to reach a conclusion.
Easy and Quickest way to learn “Hypothesis Testing” will help you to understand the concept of hypothesis testing and application of hypothesis Testing in your Research Project, Dissertation and Thesis with the help of MS Excel. It is also useful for your exam.
Easy and Quickest way to learn “Hypothesis Testing” using Ms Excel is sensibly designed for the researcher and students of social science who are struggling with Data analysis /Statistics.
This course will give guidelines about how to test hypothesis in your Research Project, Dissertation and Thesis with the help of MS Excel. The Course will improve your academic performance for your research course or Statistics course.
Do not Worry, if you don’t Have any prior knowledge of Data Analysis/Statistics. We will start from scratch.
The Course Contain 3 hour 30 minutes of video lectures.