Introduction to Hypothesis Testing - Statistical Analysis - Lecture Slides, Slides of Statistics

Download Introduction to Hypothesis Testing - Statistical Analysis - Lecture Slides and more Slides Statistics in PDF only on Docsity!

Introduction to Hypothesis

Testing

Hypotheses

A hypothesis is a prediction about the outcome of a research study

Overview of Hypothesis Testing

1. State a hypothesis about a population
   1. Usually in terms of the value of a population parameter
      1. Typically the mean or the difference between means

Overview of Hypothesis Testing --

Continued

If the data are consistent with the hypothesis, conclude that the hypothesis was reasonable, and fail to reject it

Example -- Continued

1. Obtain a random sample of women who are pregnant and smoke
2. Obtain a random sample of non-smoking pregnant women, or compare to the national average
3. Weigh the babies at birth
4. Compare sample data to hypothesis
5. Make decision:
   1. Reject the null hypothesis
   2. Fail to reject the hypothesis

Assumptions Behind Hypothesis

Testing

The effect of the Independent Variable (treatment effect) is assumed to: Add (or subtract) a constant from every individual’s score

Steps in Hypothesis Testing

1. Determine the number of samples (groups, conditions) 1. One 2. Two 3. k (three or more)

Steps in Hypothesis Testing --

continued

2. If there are two or more samples, determine whether they are independent or dependent 1. Same group (repeated-measures) 2. Match on some other variable(s) known to influence DV (matched-subjects)

Steps in Hypothesis Testing --

continued

4. Identify the independent variable
5. Identify the dependent variable and its level of measurement
6. Identify the population to which inferences will be made

Steps in Hypothesis Testing --

continued

7. Determine the appropriate inferential statistical test 1. Number of samples 2. Nature of samples (if applicable) 3. Level of measurement of DV
8. State the null hypothesis
9. State the alternative hypothesis

Null Hypothesis

The null hypothesis predicts that the Independent Variable (treatment) will have no effect on the Dependent Variable for the population

Alternative Hypothesis

The alternative hypothesis predicts that the Independent Variable (treatment) will have an effect on the Dependent Variable for the population

Non-directional Alternative

Hypotheses

Researcher has no reason to believe that there will be a difference in a specified direction

There is insufficient research or information or theory to make a specific prediction

Set the Criteria

Because of sampling error, there is likely to be a discrepancy between the sample mean and the population mean

At what point does the difference become meaningful and not just a matter of chance?