RES/710: Statistical Research Methods And Design I

Assignment InstructionsAssessment Prep

Download the Quantitative Research Foundations Dataset.

Leadership Style	Job Performance Rating	Years of Experience	Feedback Frequency
Laissez-Faire	3.4	6.9	Sometimes
Transformational	3.5	6.6	Sometimes
Laissez-Faire	2.8	9.4	Often
Laissez-Faire	2.7	6.1	Often
Transformational	4.4	10.6	Often
Transformational	5	9.5	Often
Laissez-Faire	3.1	20.5	Rarely
Transactional	3.9	5.9	Often
Laissez-Faire	2.3	6.9	Sometimes
Laissez-Faire	3.1	11.7	Rarely
Laissez-Faire	3.1	13.5	Sometimes
Laissez-Faire	5	19.1	Sometimes
Transformational	3.8	16.5	Sometimes
Laissez-Faire	2.1	13.3	Often
Transactional	1.3	11.2	Often
Transformational	2.5	13.6	Rarely
Transactional	3.7	7.6	Rarely
Transactional	3.8	8.7	Often
Transactional	4.2	4.1	Sometimes
Transactional	1.7	9.1	Rarely
Transformational	4.1	13.9	Often
Transformational	3.5	9.2	Often
Transactional	4	6.9	Often
Transactional	4.2	8.6	Sometimes
Transformational	5	12.9	Often
Transformational	4.6	9	Often
Transformational	3.6	13.4	Often
Laissez-Faire	3.9	4.8	Often
Laissez-Faire	2.5	6.5	Rarely
Laissez-Faire	2.5	8	Rarely
Transactional	1.6	4.8	Often
Laissez-Faire	2.1	21.8	Sometimes
Transactional	4.1	5.6	Rarely
Transactional	2.6	13.7	Often
Laissez-Faire	4	7.3	Rarely
Transactional	4.8	7.9	Rarely
Laissez-Faire	3.7	11.2	Sometimes
Laissez-Faire	4.1	4.2	Often
Transformational	2.6	7.3	Often
Laissez-Faire	3.4	9.4	Sometimes
Transformational	5	6.6	Sometimes
Laissez-Faire	2.4	6.7	Often
Laissez-Faire	4.5	14.3	Often
Transformational	5	14	Sometimes
Transformational	4	8.2	Rarely
Laissez-Faire	1.8	9.7	Rarely
Transactional	3.8	14.9	Sometimes
Transformational	3.4	4.3	Rarely
Transactional	4	11.4	Sometimes
Transactional	4.2	17.9	Rarely

I will use this dataset to complete this summative assessment.

Assessment Deliverable

Complete the Summative Assessment: Quantitative Research Foundations Worksheet.

Summative Assessment: Quantitative Research Foundations Worksheet

This worksheet will guide through key steps in quantitative research, including evaluating data collection methods, classifying variables, computing descriptive statistics, and interpreting your results. I will need to apply these concepts using a research study scenario, perform statistical calculations in Excel, and interpret the findings to demonstrate my understanding.

Section 1: Evaluating and Improving Data Collection

In this section, I will analyze a research scenario, evaluate the strengths and weaknesses of its data collection method, and propose an improved approach to enhance validity and reliability.

Scenario: Experience and Employee Performance

A large organization is studying how employee experience levels relate to job performance. To collect data, researchers emailed a voluntary survey to 500 employees across multiple departments. The survey asked employees to:

Rate their direct manager's leadership style (transformational, transactional, laissez-faire). Evaluate their own job performance on a scale from 1 (poor) to 5 (excellent). Report how often they receive feedback (rarely, sometimes, often). Indicate their years of experience in their current role (number).

A total of 180 employees (n = 180) responded. Researchers plan to analyze whether employee experience influences self-reported job performance.

I need help responding to the following with the scenario above in mind:

1. Describe one weakness in the data collection method that could affect the accuracy or trustworthiness of the results. Justify your response.2. Propose one change that would reduce bias or improve reliability.3. Discuss how your suggested change could improve the quality of the data.

Section 2: Classifying Variables and Levels of Measurement

In this section, you will use the research scenario to classify the variables based on their type and level of measurement. You will also explain why accurate classification is important in quantitative research

Part 1

Using the leadership study scenario, identify and classify each variable below by type (categorical or numerical) and level of measurement (nominal, ordinal, interval, or ratio).

i need to enter the responses in the table provided. An example has been included in the first row for guidance.

Variable Name	Type	Level of Measurement
Example: Leadership Style	Example: Categorial	Example: Nominal

Part 2

I need help explaining why accurately classifying variables and levels of measurement is essential in quantitative research. My explanation should be four hundred words.

Section 3: Computing and Interpreting Descriptive Statistics

In this section, you will use the Week 3 dataset to calculate and interpret descriptive statistics for the numerical variables in the research study scenario.

Part 1

Open the provided Week 3 Quantitative Research Foundations Dataset Excel file.

Calculate the following descriptive statistics for the Years of Experience and Job Performance variables. I need help solving and entering the results in the table below using my ipad.

Variable	Mean	Median	Mode	Range	Variance	Standard Deviation
Years of Experience
Job Performance

Part 2

I need help with Creating at least 1 visualization (e.g., histogram, boxplot) using Excel on my ipad and inserting it below.

Part 3

Explaining why descriptive statistics, including measures of variability, are important for understanding and interpreting the data before moving to inferential analysis.

Section 4: Interpretation

Interpreting the descriptive statistics I calculated from Section 3.

Then I have to write a short discussion in four hundred words explaining what the descriptive statistics suggest about employee experience levels and job performance.