Analyzing and Interpreting Data Quiz (Chapters 12-13)

What is the first step in analyzing qualitative data?

• Transcribing the data

• Entering the data into a program

• Creating codes for the data

• Calculating the mean of the data

What is the purpose of reducing the data in qualitative analysis?

• To organize and simplify the data

• To calculate the frequency of different answers

• To analyze the relationship between variables

• To create contingency tables

Which type of variable can be ranked but does not have a consistent interval between values?

• Interval variable

• Ordinal variable

• Nominal variable

• Bivariate variable

What is the purpose of contingency tables in bivariate data analysis?

• To calculate the mean of two variables

• To measure the correlation between two variables

• To analyze the relationship between two nominal variables

• To create a visual representation of data

What does a positive correlation between two variables indicate?

• As one variable increases, the other variable decreases

• There is no relationship between the two variables

• As one variable increases, the other variable also increases

• The variables are not related

What is the range of an interval variable?

• The minimum and maximum values of the variable

• The difference between the mean and median of the variable

• The number of times each value appears in the data

• The strength of the correlation between two variables

What is the purpose of univariate data analysis?

• To analyze the relationship between two variables

• To calculate the mean of a variable

• To summarize and describe the data

• To create contingency tables

What is the main difference between interval and ordinal variables?

• Interval variables can be ranked, while ordinal variables cannot

• Ordinal variables have a consistent interval between values, while interval variables do not

• Interval variables are measured in numbers, while ordinal variables are measured in words

• Ordinal variables can be analyzed using Pearson's r test, while interval variables cannot

What does it mean if the correlation coefficient (r) is close to 1?

• There is a strong positive correlation between the variables

• There is a strong negative correlation between the variables

• There is no correlation between the variables

• The variables are not related

What is the purpose of data display in quantitative analysis?

• To calculate the frequency of different answers

• To summarize and describe the data

• To analyze the relationship between variables

• To create a visual representation of data