Preparing Quantitative Research Data MCQs
Preparing Quantitative Research Data MCQs
The following Preparing Quantitative Research Data MCQs have been compiled by our experts through research, in order to test your knowledge of the subject of Preparing Quantitative Research Data. We encourage you to answer these multiple-choice questions to assess your proficiency.
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1: Codebook contains information about the structure of the data, such as _________.
A. Variable names
B. Labels
C. Values with their corresponding codes.
D. All of these.
2: __________ is a measure that consists of the summation of responses to hierarchically related individual questions and from which, if the scale is accurate, original question responses can be deduced.
A. Guttman scale
B. Likert scale
C. Variable label
D. Variable name
3: _________ is a summative measure where the coded response of individual questions all measuring the same dimension of a concept and which are usually individually asked in a five- to seven-point Likert format are added to produce a total value, which is the scale score.
A. Guttman scale
B. Likert scale
C. Variable label
D. Variable name
4: _________ is in a codebook, this is usually the full-working question that corresponds to a piece of data, such as a full survey question.
A. Guttman scale
B. Likert scale
C. Variable label
D. Variable name
5: ________ is usually a shortened name given to a piece of information, such as a survey question, that is used for computer identification of specific pieces of data.
A. Guttman scale
B. Likert scale
C. Variable label
D. Variable name
6: Quantitative research data preparation involves:
A. Transcribing qualitative interviews
B. Conducting statistical tests on the data
C. Cleaning, organizing, and transforming raw data into a usable format (Correct)
D. Conducting focus group discussions
7: Which of the following is a common step in data cleaning for quantitative research?
A. Transcribing audio recordings
B. Removing missing values and outliers (Correct)
C. Conducting thematic analysis
D. Coding data into themes
8: What is the purpose of data coding in quantitative research?
A. To assign numerical codes to participants
B. To convert qualitative data into quantitative data
C. To create categories and labels for different variables (Correct)
D. To conduct statistical tests on the data
9: In quantitative research, what is the role of data entry?
A. To summarize the findings of the research
B. To conduct statistical analyses
C. To input the collected data into a computer software or spreadsheet (Correct)
D. To conduct literature reviews
10: Which of the following is true about data validation in quantitative research?
A. Data validation is not necessary for quantitative research
B. Data validation involves checking the accuracy and completeness of data (Correct)
C. Data validation is only relevant for qualitative research
D. Data validation is a subjective process
11: When preparing data for analysis, what is the purpose of data transformation?
A. To remove missing values from the data
B. To convert qualitative data into quantitative data
C. To convert the data into a suitable format for analysis (Correct)
D. To create new variables for statistical tests
12: In quantitative research, what is the purpose of data reduction techniques?
A. To eliminate outliers from the data
B. To reduce the sample size for analysis
C. To simplify and summarize the data to a manageable level (Correct)
D. To replace missing values in the dataset
13: Which of the following is a common data format for quantitative research analysis?
A. Audio recordings
B. Text documents
C. Spreadsheets or databases (Correct)
D. Video files
14: In quantitative research, what is the purpose of data aggregation?
A. To remove missing values from the data
B. To combine individual data points into groups or categories (Correct)
C. To analyze the data using statistical tests
D. To convert qualitative data into quantitative data
15: What is the primary goal of preparing quantitative research data?
A. To summarize the data using descriptive statistics
B. To draw conclusions and make generalizations
C. To ensure the data is accurate, clean, and ready for analysis (Correct)
D. To transcribe qualitative interviews for analysis
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Preparing Quantitative Research Data MCQs
