Introductory Statistics for Economics and Management

Introductory Statistics for Economics and Management

Major Courses

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School of Economics and Management

All

KCCBG1MCA7

2.00Credits

講義・演習 (Lecture/Seminar)

Fall semester 2026

(Fall semester)

Jean-Baptiste SANFO

School of Economics and Management

English

1／9

Before or after class, in the classroom

sanfo@em.u-hyogo.ac.jp

1◎／2〇／3〇

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N/a

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【Course Objectives】
Statistics is a powerful tool used to make sense of data, uncover patterns, and inform decision-making. In economics, statistical skills are essential for interpreting market trends, evaluating policies, and conducting empirical research. This course provides a foundational understanding of statistics and its application to economic analysis. Throughout this course, we will explore key statistical concepts, methods, and techniques that are integral to understanding and solving real-world economic problems. We will focus on practical applications by emphasizing how statistical methods are used in economic research, policy analysis, and business decision-making.

【Learning Outcome】
By the end of this course, you will have developed critical skills to:
1. Demonstrate understanding of basic concepts of descriptive and inferential statistics
2. Apply basic concepts of descriptive and inferential statistics
3. Analyze economic data using statistical methods
4. Use statistical software to perform data analysis and present findings clearly and effectively.
5. Interpret and critically evaluate statistical results in economic research

Mean, variance,  probability, sample, population, correlation, regression

【Course Overview】

This course introduces fundamental statistical concepts and methods used in economic analysis. Students learn how to summarize data, assess uncertainty, and draw conclusions using statistical methods commonly applied in economics. Emphasis is placed on building intuition, applying methods to data, and preparing students for further study in econometrics and empirical economic research.


【Course Schedule】

Lecture 1: Guidance and Introduction to Statistics
Lecture 2: Displaying Descriptive Statistics
Lecture 3: Calculating Descriptive Statistics
Lecture 4:  Introduction to Probabilities
Lecture 5: Discrete Probability Distributions
Lecture 6: Continuous Probability Distributions
Lecture 7: Mid-term evaluation
Lecture 8: Sampling and Sampling Distributions
Lecture 9:  Confidence Intervals
Lecture 10:  Hypothesis Testing for a Single Population
Lecture 11:  Hypothesis Tests Comparing Two Populations
Lecture 12:  Analysis of Variance (ANOVA) Procedures
Lecture 13:  Chi-Square Tests
Lecture 14:  Correlation and Simple Linear Regression I
Lecture 15:  Correlation and Simple Linear Regression II

Final evaluation

The content of the course may vary depending on the pace of progress.

Hybrid (In-person)

Each topic is first introduced theoretically to ensure a solid understanding of fundamental concepts and terminology. Application of these concepts will then be performed,  followed by interpretation and discussion of the results.


For sessions conducted remotely, students must have the necessary equipment and internet access (e.g., a computer and a stable Wi-Fi connection) to attend classes from home or other locations. Sessions to be conducted remotely will be determined and communicated after course registration.

Limited permission for use

Students are required to comply with the University of Hyogo's policy regarding the use of generative AI tools. Generative AI may be used as a supplementary aid for learning activities such as drafting reports or conducting preliminary research, provided that students critically assess the content produced. Students are responsible for verifying the accuracy of all information, properly acknowledging sources and references, and ensuring that submitted work reflects their own understanding and independent effort. Assignments generated primarily by generative AI, or submitted without appropriate revision and original contribution, are not permitted.

If inappropriate use of generative AI is identified, the assignment may receive no credit or other academic measures may be taken in accordance with university regulations.

Business Statistics, 3e, by Robert A Donnelly, 2020, Pearson Education

Statistical Techniques in Business and Economics, Douglas Lind, William Marchal, and Samuel Wathen, 18e, 2020, McGraw Hill.
Statistics for Business and Economics by Paul Newbold, William L. Carlson, and Betty Thorne (Tenth Global edition).
Introduction to Statistics by Dr. Lauren Perry
https://bookdown.org/lgpperry/introstats/

【Pre-Learning】Students will be provided with lecture notes and handouts beforehand. Please read them before the class.

【Post-Learning】Lecture notes and handouts will contain exercises or questions. Please review them after the class.

Students will be asked to share their understanding of given concepts or asked to report orally what they discussed in groups.

Some concepts will be demonstrated using R, and we will discuss the output.

Engagement in classroom activities (20%)
Assignments (20%)  
Mid-term Evaluation (30%)
Final evaluation (30%)

In the classroom

This course is useful for any student interested in applying quantitative tools and techniques for data analysis.

Regular attendance is required.

N/A

Remember that making mistakes is a natural part of the learning process. Don’t fear mistakes; instead, view them as valuable opportunities for growth. Be proactive in your learning by seeking help, asking questions, and sharing your thoughts. Learning is a collaborative effort, and I’m here to support you every step of the way. Just as you are learning, so am I; together, we can create a positive and enriching experience. Let’s engage, explore, and learn from each other!