Hypothesis Testing Flashcards
It is a statement or claim regarding a characteristic of one or more populations.
Hypothesis
It is a preconceived idea, assumed to be true but has to be tested for its truth or falsity.
Hypothesis
A procedure on sample evidence and probability used to test claims regarding one or more population’s characteristics.
Hypothesis Testing
Usually expressed in terms of equality or no difference.
Null Hypothesis
It suggests that there is no significant difference in the quantitative characteristic of the population.
Null Hypothesis
Hypothesis proposed to be accepted if the sample data do not show evidence to prove null hypothesis.
Alternative Hypothesis
Implies that there is a significant difference in the quantitative characteristic of the population.
Alternative Hypothesis
How can a hypotheses be written?
- Statement form or Textual method
- Mathematical Form
Which form is expressed using equality and directional inequality, such as greater than (>), less than (<), or not equal (≠).
Mathematical Form
In testing hypotheses, what are the four cases that will have to be considered?
Hypotheses for:
1. single population
2. two populations
3. multiple populations
4. the difference in frequencies
Procedures for Testing Hypothesis
- State the null and alternative hypothesis.
- Set the level of significance or alpha level (α).
- Determine the statistical test to be used.
- Calculate the test statistic or p-value.
- Make a statistical decision.
- Draw a conclusion.
What are the two types of alternative tests?
- One-tailed test
- Two-tailed test
What does a hypothesis test cannot contain if it is used to support a claim?
Condition of equality
If a hypothesis test is used to support a claim, the claim must be what to become the alternative hypothesis?
It must be stated.
It is the probability of rejecting the null hypothesis when it is true.
Level of Significance
It is also referred to as the level of risk.
Level of Significance
What significance level is selected for consumer research projects?
0.05 level
What significance level is selected for quality assurance?
0.01 level
What significance level is selected for political polling?
0.1 level
What do we commit if we reject the null hypothesis when it is true?
Type I error (False Positive)
What do we commit if we accept the null hypothesis when it is false?
Type II error (False Negative)
The probability of committing a Type I error is designated by what?
α
The probability of committing a Type II error is designated by what?
β
Decisions and Possible Consequences
Rejecting the true null hypothesis.
Type I error (False Positive)
Decisions and Possible Consequences
Rejecting the false null hypothesis.
Correct
Decisions and Possible Consequences
Retaining the true null hypothesis.
Correct
Decisions and Possible Consequences
Retaining the false null hypothesis.
Type II error (False Negative)
They allow researchers to make inferences because they can show whether an observed pattern is due to intervention or chance.
Statistical Tests
What does the decision of which statistical test to use depends on?
- Research Design
- Distribution of the data
- Variable Type
What test should be used when data is normally distributed?
Parametric Tests
What test should be used when data is non-normal?
Non-parametric Tests
These tests look for an association between variables.
Correlational
These tests look for the difference between the means of variables.
Comparison of Means
These tests assess if the change in one variable predicts change in another variable.
Regression
Tests for the strength of the association between two continuous variables.
Pearson Correlation
Tests for the strength of the association between two ordinal variables (does not rely on the assumption of normally distributed data).
Spearman Correlation
Tests for the strength of the association between two categorical variables.
Chi-Square
Tests for the difference between two variables from the same population (e.g., a pre- and posttest score)
Paired t-test
Tests for the difference between the same variables from different populations (e.g., comparing boys and girls)
Independent t-test
Tests for the difference between group means after any other variance in the outcome variable is accounted for (e.g., controlling for sex, income, or age)
ANOVA
Tests how the change in the predictor variable predicts the level of change in the outcome variable.
Simple Regression
Tests how the change in the combination of two or more predictor variables predict the level of change in the outcome variable.
Multiple Regression
It is a number describing how likely it is that your data would have occurred under the null hypothesis of your statistical test.
P-value or Probability Value
It can be obtained by performing statistical analysis using a statistical software such as Excel, SPSS, R, Minitab, SAS, JASP, etc.
P-value or Probability Value
What is the decision rule when using p-value approach?
Reject null hypothesis is p-value is less than or equal to the set of significance level; otherwise, do not reject the null hypothesis.
What is the decision rule when using traditional method?
Reject null hypothesis if the test statistic’s computed value falls in the region of rejection.
It is the set of all values of the test statistic which leads to the rejection of null hypothesis.
Rejection Region or Critical Region
It’s a set of all values of the test statistic that leads the researcher to retain the null hypothesis.
Acceptance Region
What is the final step in hypothesis testing?
Deciding to reject or not to reject the null hypothesis.
What should be recorded in the report at the end of hypothesis testing?
- Conclusions
- Recommendations
- Interpretations (to justify the conclusion and recommendations)
