# Hypothesis Testing

Chapter

## Learning Objectives

1. 1.

Hypothesis testing evaluates the likelihood that results from a particular sample reflect those of the population from which it is drawn.

2. 2.

The null hypothesis is the entire universe of possibility that excludes the study hypothesis.

3. 3.

The distribution of sampling means is the distribution of mean values from an infinite number of samples of a specific size.

4. 4.
The distribution of sampling means has three important properties:
1. (a)

Normal distribution for large sample sizes

2. (b)

Mean equal to the population mean

3. (c)

Variation inversely related to sample size and directly related to population variation

5. 5.

The p-value for comparing the means of two samples is calculated using the mean and standard deviation of each sample.

6. 6.

The p-value is the probability of obtaining the sample result, or more extreme result, if the null hypothesis were true. A low p-value (< 0.05) therefore implies that the null hypothesis is probably false and that the study hypothesis about the population is probably true.

## Keywords

Blood Pressure Null Hypothesis Systolic Blood Pressure High Blood Pressure Population Distribution
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.