Statistics 08 Hypothesis testing part 3 Applying concepts (point estimate, z/t statistic, P-value)

#hypothesistesting #nullhypothesis #alternativehypothesis #pointestimate #pvalue #zstatistic #tstatistic #alpha #type1error #typeierror #probability #statistics #datascience
This is the third lecture in the playlist for Hypothesis testing
Previous two lectures explain on how to frame the Null Hypothesis and Alternative Hypothesis, What are type Type I and Type II errors and how to access and choose them
In this lecture we apply the concepts that we have learnt so far and additional concepts required to arrive at the decision between Null Hypothesis and Alternative Hypothesis
Explains the following steps/actions in detail
How to use to use a point estimate (single sample statistic) to judge if the population characteristic is sufficiently deviated from the hypothesized value to reject the null hypothesis
Check for normality from the sample data summary
How to use the point estimate to arrive at the P-value
How to arrive at the z or the t statistic from the point estimate
How to use the z or the t statistic and z table or the t-table to determine the P-value
How to derive z or t critical values from α
How to compare the P-value and α to make the decision between H0 and Ha
How to make the decision in three different cases where Ha takes one of the three different forms
How to apply the above steps when the population characteristic is
population proportion of success or
the population mean

Видео Statistics 08 Hypothesis testing part 3 Applying concepts (point estimate, z/t statistic, P-value) канала DataScience with HK