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PAD813Management Sciences3 Unitsintermediate

Quantitative Methods for Public Administration

This course, Quantitative Methods for Public Administration, introduces graduate students to social science research design and statistical techniques for modifying social science data. It covers quantitative approaches, statistical analysis, sampling, forecasting, and time-series analysis. Students will learn research methodologies, hypothesis testing, and data analysis using IBM SPSS software. The course aims to equip students with the skills to apply quantitative techniques in public sector decision-making and research.

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156h
Study Time
13
Weeks
12h
Per Week
intermediate
Math Level
Course Keywords
Quantitative MethodsPublic AdministrationStatistical AnalysisResearch DesignIBM SPSS

Course Overview

Everything you need to know about this course

Course Difficulty

Intermediate Level
Builds on foundational knowledge
65%
intermediate
📊
Math Level
Moderate Math
🔬
Learning Type
Hands-on Practice

Course Topics

Key areas covered in this course

1

Quantitative Methods

2

Data Analysis

3

Descriptive Statistics

4

Correlation Analysis

5

Regression Analysis

6

Probability

Total Topics6 topics

Ready to Start

No specific requirements needed

This course is designed to be accessible to all students. You can start immediately without any prior knowledge or specific preparation.

Assessment Methods

How your progress will be evaluated (3 methods)

assignments

Comprehensive evaluation of course material understanding

Written Assessment

tutor-marked assessments

Comprehensive evaluation of course material understanding

Written Assessment

final examination

Comprehensive evaluation of course material understanding

Written Assessment

Career Opportunities

Explore the career paths this course opens up for you

Data Analyst

Apply your skills in this growing field

Statistician

Apply your skills in this growing field

Public Policy Analyst

Apply your skills in this growing field

Research Officer

Apply your skills in this growing field

Management Consultant

Apply your skills in this growing field

Industry Applications

Real-world sectors where you can apply your knowledge

Government AgenciesNon-Profit OrganizationsResearch InstitutionsConsulting FirmsHealthcare Administration

Study Schedule Beta

A structured 13-week journey through the course content

Week
1

Module 1: Introduction

2h

Unit 1: Concept of Quantitative Methods/ Techniques

2 study hours
  • •Define quantitative methods/techniques
  • •Identify the relevance of quantitative methods
  • •Understand the tools used in quantitative analysis
Week
2

Module 1: Introduction

2h

Unit 2: Data and Data Analysis

2 study hours
  • •Define data and raw data
  • •Explain types of data (quantitative, qualitative)
  • •Outline data classification methods
Week
3

Module 1: Introduction

2h

Unit 3: Graphical Technique of Quantitative Methods

2 study hours
  • •Draw and analyze frequency tables and graphs
  • •Draw and analyze histograms
  • •Explain frequency polygons
Week
4

Module 1: Introduction

2h

Unit 4: Descriptive Statistics

2 study hours
  • •Define descriptive statistics
  • •Explain cumulative frequency distribution and ogives
  • •Draw and explain pie charts, bar charts, and line charts
Week
5

Module 1: Introduction

2h

Unit 5: Measure of Central Tendency

2 study hours
  • •Discuss measures of central tendency
  • •State types of measures (mean, median, mode)
  • •Analyze mean for grouped data
  • •Calculate mode for grouped data
Week
6

Module 2: Statistical Tools

2h

Unit 1: Statistical Tools I

2 study hours
  • •Calculate range, mean deviation, variance, and standard deviation
  • •Compute measures of skewness
Week
7

Module 2: Statistical Tools

2h

Unit 2: Statistical Tools II

2 study hours
  • •Calculate variance and standard deviation for grouped data
  • •Calculate coefficient of variation
  • •Calculate Pearson's coefficients of skewness
Week
8

Module 2: Statistical Tools

2h

Unit 3: Statistical Tools III

2 study hours
  • •Define sets and subsets
  • •Explain set theory and its use in probability analysis
  • •Explain set enumerations and their application in solving business problems
Week
9

Module 2: Statistical Tools

2h

Unit 4: Statistical Tools IV

2 study hours
  • •Define probability
  • •State and apply the laws of probability
  • •Calculate probabilities
  • •Apply probabilities in making decisions involving uncertainties
Week
10

Module 2: Statistical Tools

2h

Unit 5: Basic Advance Mathematics

2 study hours
  • •Define basic algebra and its rules
  • •Calculate linear equations
  • •Calculate quadratic formulas (factorization and formula method)
  • •Apply quadratic formulas to decision making
Week
11

Module 3: Regression and Correlation

4h

Unit 1: Population vs. Sample

2 study hours
  • •Explain population vs. sample
  • •Describe data collection from population and sample
  • •Reasons for sampling

Unit 2: Correlation Analysis

2 study hours
  • •Describe computation of linear correlation coefficients
  • •Explain computation of rank correlation coefficients
  • •Apply the concept of correlations in business decisions
Week
12

Module 3: Regression and Correlation

4h

Unit 3: Simple Linear Regression

2 study hours
  • •Define and calculate linear regression
  • •Calculate simple linear regression
  • •Find the line of best fit
  • •Calculate the coefficient of determination

Unit 4: Multiple Linear Regressions

2 study hours
  • •State the multiple linear regression model
  • •Interpret model output
  • •State assumptions of multiple linear regressions
Week
13

Module 3: Regression and Correlation

2h

Unit 5: Spearman's Rank Correlation

2 study hours
  • •State the meaning of Spearman's rank correlation coefficient
  • •Explain Spearman's rank correlation scenarios
  • •Interpret statistical software for correlation coefficients

This study schedule is in beta and may not be accurate. Please use it as a guide and consult the course outline for the most accurate information.

Course PDF Material

Read the complete course material as provided by NOUN.

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Study Tips & Exam Preparation

Expert tips to help you succeed in this course

1

Review all units, focusing on key concepts and formulas.

2

Practice data analysis using IBM SPSS with provided datasets.

3

Create concept maps linking statistical techniques to research questions.

4

Solve practice problems from each unit to reinforce understanding.

5

Allocate time for thorough review of assignments and tutor-marked assessments.

6

Focus on understanding the assumptions and limitations of each statistical method.

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