Introduction

Hypothesis testing is a statistical procedure used to test assumptions or hypotheses about a population parameter.

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The primary purpose of hypothesis testing is to make inferences about a population based on a sample of data

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We start by defining the Null and Alternative Hypothesis

Null & Alternative Hypothesis

Null Hypothesis (denoted by $H_0$) states that there is no difference between groups or no relationship between variables.

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Null hypothesis defines the condition that the we need to discredit before suggesting an effect exists.

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Research Question: As screen time increases, does test performance decrease?

Null Hypothesis: There is no relationship between screen time and test performance.

Null Hypothesis can also be the claim being made: for example, a pharmaceutical company claiming that their drug can treat diabetes in 90% of the patients.

Alternative Hypothesis, (denoted by $H_1$) states that states that there is a relationship between variables.

Hypothesis Testing Mechanism

Step 1: Formulate the Null Hypothesis, $H_0$

Step 2: Formulate the Alternative Hypothesis, $H_1$

Step 3: Perform experiments (statistical analysis): this is the step where we obtain the $P$ value

Step 4: Based on the $P$ value, Accept or Reject $H_0$