Ch. 14: Analyze Quantitative & Qualitative Data

A correlation coefficient that is positive means:

1. As one variable increases, the second variable also increases 2. As one variable decreases, the second variable also decreases

Differences between qualitative and quantitative data analysis are that qualitative data analysis:

1. Begins during the collection of data 2. Is circular 3. Is iterative

Strategies for making conclusions from qualitative data include

1. Clustering 2. Counting 3. Making metaphors

Meta-data are:

1. Data about data 2. New words and/or graphic representations about original data 3. Created in qualitative data analysis

Frequency Distributions:

1. Describe how data are distributed in the sample 2. List the variables and the number of responses to each 3. Show the location of any individual response relative to all the others in a data set

Information collected in a research study comes in the form of:

1. Numbers 2. Words

In verifying conclusions, explanations are tested by:

1. Replication of findings 2. Checking rival conclusions

In order to select the appropriate statistical tool to analyze quantitative data you first must know:

1. The level of numerical measurement 2. Whether variables are measured as nominal, ordinal, interval, or ratio levels

Qualitative Data analysis requires:

An inductive thinking process

Computer assistance in analyzing qualitative data:

Do not replace researcher insights about what the findings mean

A correlation coefficient:

Is a numerical index of the relationship between two variables

The data display type that is helpful to understanding the connections among bits of information is called:

Matrix

In assuring the quality of qualitative data, we should:

Member Check

An example of a ratio measurement level is:

Number of sick days called in during the past calendar year

The first step in the qualitative data analysis process is:

Preparing expanded accounts

Describing data with measures of central tendency:

Presents the frequency distribution's center using a single value

Relative comparisons can be described by determining:

Rates and percentages

The most precise measure of variability is the:

Standard Deviation

For analyzing quantitative data:

Univariate statistics focus on one variable at a time

In managing qualitative data, one strategy is to use memoing, which is:

Writing notes that suggest explanations on the expanded accounts