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Statistical Analysis > Hypothesis Testing > Flashcards

Hypothesis Testing Flashcards

1
Q

It is a statement or claim regarding a characteristic of one or more populations.

A

Hypothesis

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2
Q

It is a preconceived idea, assumed to be true but has to be tested for its truth or falsity.

A

Hypothesis

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3
Q

A procedure on sample evidence and probability used to test claims regarding one or more population’s characteristics.

A

Hypothesis Testing

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4
Q

Usually expressed in terms of equality or no difference.

A

Null Hypothesis

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5
Q

It suggests that there is no significant difference in the quantitative characteristic of the population.

A

Null Hypothesis

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6
Q

Hypothesis proposed to be accepted if the sample data do not show evidence to prove null hypothesis.

A

Alternative Hypothesis

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7
Q

Implies that there is a significant difference in the quantitative characteristic of the population.

A

Alternative Hypothesis

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8
Q

How can a hypotheses be written?

A
  1. Statement form or Textual method
  2. Mathematical Form
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9
Q

Which form is expressed using equality and directional inequality, such as greater than (>), less than (<), or not equal (≠).

A

Mathematical Form

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10
Q

In testing hypotheses, what are the four cases that will have to be considered?

A

Hypotheses for:
1. single population
2. two populations
3. multiple populations
4. the difference in frequencies

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11
Q

Procedures for Testing Hypothesis

A
  1. State the null and alternative hypothesis.
  2. Set the level of significance or alpha level (α).
  3. Determine the statistical test to be used.
  4. Calculate the test statistic or p-value.
  5. Make a statistical decision.
  6. Draw a conclusion.
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12
Q

What are the two types of alternative tests?

A
  1. One-tailed test
  2. Two-tailed test
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13
Q

What does a hypothesis test cannot contain if it is used to support a claim?

A

Condition of equality

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14
Q

If a hypothesis test is used to support a claim, the claim must be what to become the alternative hypothesis?

A

It must be stated.

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15
Q

It is the probability of rejecting the null hypothesis when it is true.

A

Level of Significance

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16
Q

It is also referred to as the level of risk.

A

Level of Significance

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17
Q

What significance level is selected for consumer research projects?

A

0.05 level

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18
Q

What significance level is selected for quality assurance?

A

0.01 level

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19
Q

What significance level is selected for political polling?

A

0.1 level

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20
Q

What do we commit if we reject the null hypothesis when it is true?

A

Type I error (False Positive)

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21
Q

What do we commit if we accept the null hypothesis when it is false?

A

Type II error (False Negative)

22
Q

The probability of committing a Type I error is designated by what?

A

α

23
Q

The probability of committing a Type II error is designated by what?

A

β

24
Q

Decisions and Possible Consequences

Rejecting the true null hypothesis.

A

Type I error (False Positive)

25
Q

Decisions and Possible Consequences

Rejecting the false null hypothesis.

A

Correct

26
Q

Decisions and Possible Consequences

Retaining the true null hypothesis.

A

Correct

27
Q

Decisions and Possible Consequences

Retaining the false null hypothesis.

A

Type II error (False Negative)

28
Q

They allow researchers to make inferences because they can show whether an observed pattern is due to intervention or chance.

A

Statistical Tests

29
Q

What does the decision of which statistical test to use depends on?

A
  1. Research Design
  2. Distribution of the data
  3. Variable Type
30
Q

What test should be used when data is normally distributed?

A

Parametric Tests

31
Q

What test should be used when data is non-normal?

A

Non-parametric Tests

32
Q

These tests look for an association between variables.

A

Correlational

33
Q

These tests look for the difference between the means of variables.

A

Comparison of Means

34
Q

These tests assess if the change in one variable predicts change in another variable.

A

Regression

35
Q

Tests for the strength of the association between two continuous variables.

A

Pearson Correlation

36
Q

Tests for the strength of the association between two ordinal variables (does not rely on the assumption of normally distributed data).

A

Spearman Correlation

37
Q

Tests for the strength of the association between two categorical variables.

A

Chi-Square

38
Q

Tests for the difference between two variables from the same population (e.g., a pre- and posttest score)

A

Paired t-test

39
Q

Tests for the difference between the same variables from different populations (e.g., comparing boys and girls)

A

Independent t-test

40
Q

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)

A

ANOVA

41
Q

Tests how the change in the predictor variable predicts the level of change in the outcome variable.

A

Simple Regression

42
Q

Tests how the change in the combination of two or more predictor variables predict the level of change in the outcome variable.

A

Multiple Regression

43
Q

It is a number describing how likely it is that your data would have occurred under the null hypothesis of your statistical test.

A

P-value or Probability Value

44
Q

It can be obtained by performing statistical analysis using a statistical software such as Excel, SPSS, R, Minitab, SAS, JASP, etc.

A

P-value or Probability Value

45
Q

What is the decision rule when using p-value approach?

A

Reject null hypothesis is p-value is less than or equal to the set of significance level; otherwise, do not reject the null hypothesis.

46
Q

What is the decision rule when using traditional method?

A

Reject null hypothesis if the test statistic’s computed value falls in the region of rejection.

47
Q

It is the set of all values of the test statistic which leads to the rejection of null hypothesis.

A

Rejection Region or Critical Region

48
Q

It’s a set of all values of the test statistic that leads the researcher to retain the null hypothesis.

A

Acceptance Region

49
Q

What is the final step in hypothesis testing?

A

Deciding to reject or not to reject the null hypothesis.

50
Q

What should be recorded in the report at the end of hypothesis testing?

A
  1. Conclusions
  2. Recommendations
  3. Interpretations (to justify the conclusion and recommendations)

Statistical Analysis (10 decks)

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