Summative Assessment: Quantitative Research Foundations Worksheet
This worksheet will guide you through key steps in quantitative research, including evaluating data collection methods, classifying variables, computing descriptive statistics, and interpreting your results. You will apply these concepts using a research study scenario, perform statistical calculations in Excel, and interpret your findings to demonstrate your understanding.
Section 1: Evaluating and Improving Data Collection
In this section, you 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.
Respond 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).
Enter your responses in the table provided. An example has been included in the first row to guide you.
Variable Name Type Level of Measurement
Example: Leadership Style Example: Categorial Example: Nominal

Part 2
Explain why accurately classifying variables and levels of measurement is essential in quantitative research. Your explanation should be 175–350 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. Enter your results in the table below.
Variable Mean Median Mode Range Variance Standard Deviation
Years of Experience
Job Performance
Part 2
Create at least 1 visualization (e.g., histogram, boxplot) using Excel and insert it below.
Part 3
Explain why descriptive statistics, including measures of variability, are important for understanding and interpreting the data before moving to inferential analysis.
Section 4: Interpretation
Interpret the descriptive statistics you calculated from Section 3.
Write a short discussion of 175–350 words explaining what the descriptive statistics suggest about employee experience levels and job performance.

Would you like to discuss this project or get it done? 

Reach out on WHATSapp at +1 (240) 389-5520

Or 
 Place an order on our website for quick help

Guarantees

A+ Paper
 Timely Delivery
 Zero Plagiarism
 Zero AI