Quantitative Data Analysis in Urban Studies

Study Flashcards Play Quiz

Questions and Answers

Which measure of central tendency is the most resistant to outliers?

Median

What statistical measure can be used to determine the strength of the relationship between two variables?

Pearson's r

What type of analysis examines one variable at a time and involves creating frequency tables?

Univariate analysis

Which statistical measure shows the difference between the highest and lowest scores in a dataset?

$ ext{Range}$ Signup and view all the answers

What is used to determine if a sample finding is representative of the population in statistical analysis?

$ ext{Statistical significance}$ Signup and view all the answers

Which type of error in statistical analysis involves rejecting a true null hypothesis?

Type I error Signup and view all the answers

Which type of variable can be rank ordered?

Ordinal Signup and view all the answers

What kind of operations can be performed with nominal variables?

Logical operations Signup and view all the answers

Which variable type allows for arithmetic operations?

Interval Signup and view all the answers

In what way do nominal variables differ from ordinal variables?

Ordinal variables represent a ranking or order, while nominal variables do not. Signup and view all the answers

Which type of variable has categories that cannot be ordered by rank?

Nominal Signup and view all the answers

What is the biggest mistake in quantitative research according to the text?

To delay data analysis decisions until after data collection. Signup and view all the answers

What does the chi-square (Χ2) measure in contingency tables?

The likelihood of a relationship between the two variables in the population Signup and view all the answers

How is the chi-square value affected by sample size?

It is affected by sample size Signup and view all the answers

What does the F statistic indicate in analysis of variance?

Total amount of variation in the dependent variable Signup and view all the answers

How is statistical significance reported in comparing means?

$p$-value Signup and view all the answers

What does comparing means focus on?

Explained variation and error variance Signup and view all the answers

In what way does chi-square measure the relationship between variables?

It compares observed frequency with expected frequency by chance Signup and view all the answers

What does ANOVA's F-statistic indicate about variation?

The total amount of variation in dependent variable compared to independent variable Signup and view all the answers

How is statistical significance reported when comparing means?

$p$-value Signup and view all the answers

Studying That Suits You

Use AI to generate personalized quizzes and flashcards to suit your learning preferences.

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.