# Hypothesis Testing YouTube Lecture Handouts for Competitive Exams

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## Hypothesis Testing

Types of Errors & p-Region

## Null Versus Alternative Hypothesis

## Null Hypothesis (H_{0})

- No statistical significance between the two variables.
- Researcher is trying to disprove it.
- Individual is free from disease
- Relationship is due to chance

## Alternative Hypothesis (H_{a})

- Statistical significance between the two variables.
- Researcher is trying to approve it
- Individual has disease
- Relationship is not due to chance
- If is accepted, is rejected

## P-Region

## Errors in Hypothesis

True | |

Decision About
| CORRECT |

Decision About
| Type I Error (α) |

## Type I Error

- Reject when its true
- α error
- Error of first kind
- Error of excessive credulity
- False positive
- Poor specificity
- If a test shows that a person has kidney stone when in reality he/she does not

## P-Value

- Probability of obtaining an effect at least as extreme as the one in your sample data, assuming the truth of the null hypothesis.

## Errors in Hypothesis

True | False | |

Decision About
| CORRECT | Type II Error |

Decision About
| Type I Error (α) | CORRECT |

## Type II Error

- Accept H_0 when its false
- β error
- Error of second kind
- Error of excessive skepticism
- False negative
- Low sensitivity
- If a test shows that a person is not having kidney stone when in reality he/she does have a kidney stone.

✍ Manishika