BUSI 820 LIBERTY UNIVERSITY Quantitative_Analysis_Data_Coding_Entry_and_Checking_2024.pdf

QUANTITATIVE ANALYSIS: DATA CODING, ENTRY, AND CHECKING 1

Marcos Reis Campos, MBA

BUSI 820

Liberty University

May 19, 2024

QUANTITATIVE ANALYSIS: DATA CODING, ENTRY, AND CHECKING 2

Interpretation Questions: Chapter 2.................................................................................................3

A1. 2.1. Steps/actions taken after data collection and before running analyses to answer research

questions/testing research hypotheses?............................................................................................3

A1. 2.2. Why should you label the values of nominal variables?....................................................4

A1. 2.6. (b) What are ways to check data before/after entering them?...........................................5

SPSS Problems: Chapter 2...............................................................................................................6

2.1 (a) Compute N, minimum, maximum, and mean for all variables............................................6

2.1 (b) How many students have complete data?............................................................................6

2.1 (c) Identify any statistics on the output that are not meaningful. Explain.................................6

2.2 (d) What is the mean height of the students?.............................................................................6

2.2 (e) What about the average height of the same-sex parent?......................................................7

2.2 (f) What percentage of students are males?...............................................................................7

2.2 (g) What percentage have children?..........................................................................................7

References........................................................................................................................................8

QUANTITATIVE ANALYSIS: DATA CODING, ENTRY, AND CHECKING 3

Chapter 2

A1. 2.1. Steps/actions taken after data collection and before running analyses to answer

research questions/testing research hypotheses?

In order to prepare data for subsequent procedures, it is necessary to consolidate and

prepare the data for analysis. Some examples include:

● Generation of databases

● Input of data into a computing system.

● Eliminating data

● Handling incomplete or absent data

● Assigning a desired outcome through the modification or manipulation of data is referred

to as "data manipulation."

● By analyzing, cleansing, manipulating, and modeling data, the objective of data analysis

is to uncover insights, draw conclusions, and facilitate decision-making.

The extent and magnitude of empirical investigations are limited. As researchers, our

QUANTITATIVE ANALYSIS: DATA CODING, ENTRY, AND CHECKING 4

Detail-oriented note-taking will prove advantageous to both your future self and any

other individual assessing your study. Your future personality is an integral component of this.

Time will pass and the entire data set will become more difficult to comprehend, as the absence

of identifiers will obscure the data's true significance. Moreover, more comprehensible outcomes

information. Comprehensive details are presented with respect to the subsequent: the precise

recording procedure for the variable in the raw data, the units of measurement, the numerical

coding scheme, and the definitions of the numerical codes; the conceptual definition of the

variable; and the measurement methodology employed. In addition to data collection and

arrangement procedures, codebooks may encompass documentation pertaining to the time period

and methodology employed. A well-organized codebook facilitates the comprehension and

exposition of research findings in a succinct and comprehensible manner (Morgan et al., 2020).

Increasing the likelihood of comprehending and appropriately evaluating the data is enhanced.

A1. 2.4. What if data file contains words/letters instead of numbers?

Recoderization becomes necessary when input consists of letters or words as opposed to

QUANTITATIVE ANALYSIS: DATA CODING, ENTRY, AND CHECKING 5

A1. 2.5. Why use Mean to create a variable?

After the participants have completed the data collection items, the "Mean" function of

SPSS is utilized to compute the mean score of a scale or construct comprising multiple queries.

In the dataset, SPSS will compute the mean by averaging all responses, irrespective of the

investigation, dread, consists of seven distinct components, this is the case. Utilizing an item's

mean can help determine its overall average (Morgan et al., 2020).

A1. 2.6. (a) Why is it important to check raw data before/after entering them?

It is imperative to conduct a thorough data validation and verification process prior to

inputting the questionnaire responses into the data editor. A final review must be performed prior

to inputting the data into the editor. This provides an opportunity to rectify any errors that may

have occurred during the data entry procedure, thereby safeguarding it against blunders. You will

have the opportunity to rectify any errors or omissions that occurred during the initial phase of

data verification.

A1. 2.6. (b) What are ways to check data before/after entering them?

QUANTITATIVE ANALYSIS: DATA CODING, ENTRY, AND CHECKING 6

one of the previously mentioned features. Additionally, prior to inputting the data into the data

editor, you can verify the accuracy of the information by performing a cursory review. Reexecute

the program to verify that every variable and label are accurate. Verify the data for accuracy

through visual inspection once the data submission process is complete. You might observe the

SPSS Problems

Chapter 2

Using the CollegeStudentData.sav file do the following problems.

Print your outputs and circle the key parts for discussion

2.1 (a) Compute N, minimum, maximum, and mean for all variables.

2.1 (b) How many students have complete data?

2.1 (c) Identify any statistics on the output that are not meaningful. Explain.

Because it is inherently unethical to know the television viewing patterns of another

person, it is improper for an individual to possess such knowledge. Specific information

QUANTITATIVE ANALYSIS: DATA CODING, ENTRY, AND CHECKING 7

2.2 (e) What about the average height of the same-sex parent?

66.78 = 5’56”

2.2 (f) What percentage of students are males?

QUANTITATIVE ANALYSIS: DATA CODING, ENTRY, AND CHECKING 8

References

Dupont, W. D. (2021). Review of michael N. Mitchell’s data management using stata: A

practical handbook, second edition. The Stata Journal, 21(3), 814-817.

https://doi.org/10.1177/1536867X211045581

https://doi.org/10.1097/MLR.0000000000001146

Morgan, G. A., Barrett, K. C., Leech, N. L., & Gloeckner, G. W. (2020). IBM SPSS for

Introductory Statistics Use and Interpretation (6th ed.). New York, NY, USA: Routledge.

QUANTITATIVE ANALYSIS: DATA CODING, ENTRY, AND CHECKING 9

Figure 1: 2.3 – Codebook

QUANTITATIVE ANALYSIS: DATA CODING, ENTRY, AND CHECKING