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Questions and Answers
Which statistical test is used to compare two sample means for continuous data?
Which statistical test is used to compare two sample means for continuous data?
What summarizes the strength of the association between a risk factor and a disease?
What summarizes the strength of the association between a risk factor and a disease?
In hypothesis testing, what is Step 3 about?
In hypothesis testing, what is Step 3 about?
Which test is the non-parametric equivalent to the independent sample t test?
Which test is the non-parametric equivalent to the independent sample t test?
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What is used to investigate the bivariate associations with continuous variables?
What is used to investigate the bivariate associations with continuous variables?
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What type of error is related to rejecting a true null hypothesis?
What type of error is related to rejecting a true null hypothesis?
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What does SPSS do when calculating the 5% trimmed mean?
What does SPSS do when calculating the 5% trimmed mean?
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How is normality tested in the output from Descriptive?
How is normality tested in the output from Descriptive?
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What does the boxplot provided in the output show?
What does the boxplot provided in the output show?
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How does the choice of inferential statistical test depend on the distribution of the data?
How does the choice of inferential statistical test depend on the distribution of the data?
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What type of test would be used to compare the BMI between two groups at baseline?
What type of test would be used to compare the BMI between two groups at baseline?
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What is the significance level typically set at for parametric tests?
What is the significance level typically set at for parametric tests?
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If the authors wanted to compare BMI between two groups at baseline using non-parametric tests, which test should they have used?
If the authors wanted to compare BMI between two groups at baseline using non-parametric tests, which test should they have used?
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What does the Levene's test for Equality of Variances assess in the context of the independent samples t-test?
What does the Levene's test for Equality of Variances assess in the context of the independent samples t-test?
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Study Notes
Comparing Sample Means
- The independent sample t-test is used to compare two sample means for continuous data.
Risk Factor and Disease Association
- The odds ratio summarizes the strength of the association between a risk factor and a disease.
Hypothesis Testing
- Step 3 in hypothesis testing involves specifying the null and alternative hypotheses.
Non-Parametric Tests
- The Mann-Whitney U test is the non-parametric equivalent to the independent sample t-test.
Bivariate Associations
- Scatter plots are used to investigate the bivariate associations with continuous variables.
Errors in Hypothesis Testing
- Type I error is related to rejecting a true null hypothesis.
Calculating Trimmed Mean in SPSS
- When calculating the 5% trimmed mean in SPSS, it removes 5% of the lowest and 5% of the highest values from the dataset.
Normality Testing
- Normality is tested in the output from Descriptive using the Shapiro-Wilk test.
Box Plot Interpretation
- The boxplot provided in the output shows the distribution of the data, including outliers and skewness.
Choosing Statistical Tests
- The choice of inferential statistical test depends on the distribution of the data, with parametric tests used for normal data and non-parametric tests used for non-normal data.
Comparing Group Means
- The independent sample t-test would be used to compare the BMI between two groups at baseline.
Significance Level
- The significance level is typically set at 0.05 (5%) for parametric tests.
Non-Parametric Tests for Group Comparison
- If the authors wanted to compare BMI between two groups at baseline using non-parametric tests, they should have used the Mann-Whitney U test.
Levene's Test
- Levene's test for Equality of Variances assesses whether the variances of the two groups are equal, which is an assumption of the independent samples t-test.
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Description
This quiz covers topics such as boxplots analysis, interpreting falls efficacy data, summarizing continuous data, converting findings into text, and preparing for inferential statistical analysis with a focus on hypothesis testing.