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Questions and Answers
Which measure of central tendency is the most resistant to outliers?
Which measure of central tendency is the most resistant to outliers?
What statistical measure can be used to determine the strength of the relationship between two variables?
What statistical measure can be used to determine the strength of the relationship between two variables?
What type of analysis examines one variable at a time and involves creating frequency tables?
What type of analysis examines one variable at a time and involves creating frequency tables?
Which statistical measure shows the difference between the highest and lowest scores in a dataset?
Which statistical measure shows the difference between the highest and lowest scores in a dataset?
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What is used to determine if a sample finding is representative of the population in statistical analysis?
What is used to determine if a sample finding is representative of the population in statistical analysis?
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Which type of error in statistical analysis involves rejecting a true null hypothesis?
Which type of error in statistical analysis involves rejecting a true null hypothesis?
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Which type of variable can be rank ordered?
Which type of variable can be rank ordered?
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What kind of operations can be performed with nominal variables?
What kind of operations can be performed with nominal variables?
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Which variable type allows for arithmetic operations?
Which variable type allows for arithmetic operations?
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In what way do nominal variables differ from ordinal variables?
In what way do nominal variables differ from ordinal variables?
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Which type of variable has categories that cannot be ordered by rank?
Which type of variable has categories that cannot be ordered by rank?
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What is the biggest mistake in quantitative research according to the text?
What is the biggest mistake in quantitative research according to the text?
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What does the chi-square (Χ2) measure in contingency tables?
What does the chi-square (Χ2) measure in contingency tables?
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How is the chi-square value affected by sample size?
How is the chi-square value affected by sample size?
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What does the F statistic indicate in analysis of variance?
What does the F statistic indicate in analysis of variance?
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How is statistical significance reported in comparing means?
How is statistical significance reported in comparing means?
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What does comparing means focus on?
What does comparing means focus on?
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In what way does chi-square measure the relationship between variables?
In what way does chi-square measure the relationship between variables?
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What does ANOVA's F-statistic indicate about variation?
What does ANOVA's F-statistic indicate about variation?
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How is statistical significance reported when comparing means?
How is statistical significance reported when comparing means?
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Study Notes
- The text discusses data analysis techniques, specifically univariate and bivariate analysis, measures of central tendency and dispersion, and statistical significance.
- Univariate analysis examines one variable at a time, and involves creating frequency tables to understand the distribution of the variable. Frequency tables can be used to illustrate the distribution using diagrams such as bar charts and pie charts.
- Measures of central tendency include the mode, median, and mean. The mode is the most frequent score, the median is the middle score, and the mean is the average.
- Measures of dispersion include the range and standard deviation. The range shows the difference between the highest and lowest scores, while standard deviation measures the spread of the data around the mean.
- Bivariate analysis examines two variables at a time and determines if there is a relationship between them. Contingency tables and correlation coefficients are used for this analysis.
- Contingency tables allow simultaneous analysis of two variables and identify patterns of association. Pearson's r, Kendall's tau-b, and Spearman's rho are correlation coefficients used to determine the strength of the relationship between variables.
- Eta, Kendall's tau-b, Spearman's rho, and Pearson's r squaring show the amount of explained variance between two variables. These measures allow prediction of the second variable based on the score from the first.
- Statistical significance is used to determine if a sample finding is representative of the population. A null hypothesis testing the significance of the bivariate association is set up, and an acceptable level of significance (≤.05) is established. If the null hypothesis is rejected and the statistical significance (p) is ≤.05, there is indirect support for the research hypothesis.
- There are two types of errors in statistical analysis: Type I (rejecting a true null hypothesis) and Type II (not rejecting a false null hypothesis). Researchers usually choose to minimize Type I error over Type II.
- Correlation and statistical significance must be weighed together in interpreting the results, as statistical significance only speaks to the results not occurring by chance alone and does not speak to the importance of the results.
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Description
Learn about quantitative data analysis in urban studies, including types of variables, univariate analysis, and bivariate analysis. Get feedback on research questions and an introduction to quantitative methods.