Malik_BUSI820_Assignment1

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School of Business, Liberty University Faizan Malik Quantitative Analysis: Data Coding, Entry, and Checking Author Note: Faizan Malik I have no known conflict of interest to disclose. Correspondence concerning this article should be addressed to Faizan Malik: Fmalik@Liberty.edu

BUSI820 Assignment 1 Table of Contents QUANTITATIVE ANALYSIS: DATA CODING, ENTRY, AND CHECKING 3 Interpretation Questions 3 SPSS Problems 7 References 8 2

BUSI820 Assignment 1 QUANTITATIVE ANALYSIS: DATA CODING, ENTRY, AND CHECKING Interpretation Questions Chapter 2 A1. 2.1. What steps or actions should be taken after you collect data and before you run the analyses aimed at answering your research questions or testing your research hypotheses? A1. 2.1a Prior to data analysis, Morgan et al. (2020), suggests that collected data be reviewed for any potential errors or inconsistencies, including the questionaries themselves and contingency plans for missing data (Morgan et al., 2020). Researchers should then work to code their data, through various process of creation and modification, as this ensures that the format is suitable for analysis (Morgan et al.,2020). Collectively, these steps help researchers present their findings in a standardized format. A1. 2.2. Why should you label the values of nominal variables? A1. 2.2a Morgan et al. (2020) provides several benefits of labeling nominal variables including improvements in interpretation by avoiding general naming, data documentation by assigning each dataset a purpose with content, data analysis by providing clarity to the reader, data visualization through the means of graphs and other visuals (Morgan et al., 2020). A1. 2.3. Why would you print a codebook or dictionary? A1. 2.3a Codebooks act as essential dictionaries for data for researchers, organizing variables that exist within a dataset along with their meanings and the overall coding scheme used within a study (Morgan et al., 2020). Printing codebooks provides value in 3

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BUSI820 Assignment 1 quality control, ensuring data accuracy, and in instances of collaborative research, in which multiple researchers can refer to a single reference (Morgan et al., 2020). A1. 2.4. What do you do if you look at your data file and see words or letters instead of numbers? Why is this important to do? A1. 2.4a Seeing text in the place of numeric values within a data file indicates that the variable is being entered as a string or text variable instead of a numeric variable. To correct this, researchers must first ensure that their data is free of errors and then recode their data into a numeric variable, as this allows for accurate data analysis. If, however, there is no issue with the data itself, the issue may be error with importing data (Morgan et al., 2020). A1. 2.5. Why would you use the Mean function to create a variable, as we did for the pleasure scale? A1. 2.5a The mean function serves to aggregate multiple variables into a single variable, thus allowing a single variable to represent the overall average which simplifies the data analysis process. A mean value for a dataset also serves to provide more reliable data, as an average response across all items are considered which reduces the risk associated with potential measurement errors (Morgan et al., 2020). A1. 2.6. (a)Why is it important to check your raw (questionnaire) data before and after entering them into the data editor? (b) What are ways to check the data before entering them? After entering them? A1. 2.6a Reviewing questionnaires both before and entering entry into a data editors allows researchers to ensure greater levels of data accuracy by finding potential errors 4

BUSI820 Assignment 1 and identifying areas of missing data, which can both impact the validity of a study (Morgan et al., 2020). A1. 2.6b To review data before entry, Morgan et al. (2020) suggests researchers begin with a pre-entry data review, in which the dataset is comprehensively reviewed for any potential errors. The author also provides an additional processes of double data entry, in which data is entered by two separate individuals to identify potential discrepancies, and data coding checks if required (Morgan et al., 2020). After data entry, Morgan et al. (2020), provides that researchers perform various checks for range and value to evaluate outliers within the data, consistency, and missing data, which collectively can assist with cross validation of data (Morgan et al., 2020). 5

BUSI820 Assignment 1 SPSS Problems Chapter 2 6

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BUSI820 Assignment 1 Compute the N, minimum, maximum, and mean for all the variables 7

BUSI820 Assignment 1 How many students have complete data? 47 of the 50 participants have complete data. Identify any statistics on the output that are not meaningful. Explain. Of all possible outputs for this study, those centered around viewing preference (comedy, movies, sports, news) seem to be the least meaningful as it would not be relevant to physical attributes of the children. What is the mean height of the students? 67.3 What about the average height of the same-sex parent? 8

BUSI820 Assignment 1 68.70 What percentage of students are males? 52% What percentage have children? 52% References Morgan, G., Leech, N., Gloeckner, G., Barrett, K. (2020). IBM SPSS for Introductory Statistics (5th Ed.). New York, NY 9

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