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BUSI 1030: Data Analysis and Interpretation – Syllabus Overview and Topic Guide

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Course Overview

Introduction to Statistics for Business

This course provides a foundational understanding of statistics and data analysis for business students. It covers essential topics such as data types, descriptive statistics, probability, distributions, sampling, hypothesis testing, correlation, regression, and ANOVA. The course emphasizes both theoretical concepts and practical applications relevant to business decision-making.

  • Course Objective: Develop critical thinking and problem-solving skills using statistical methods for effective business decision-making.

  • Applications: Real-world business scenarios, including data-driven decision processes and interpretation of statistical results.

Course Topics and Schedule

Major Topics Covered

The syllabus outlines a progression through the following key chapters, each corresponding to a major area in business statistics:

Date

Topic

Aug 18

Introduction and Chapter 1 (Types of data and sampling techniques)

Aug 23

Chapter 2 (Describing data with tables and graphs)

Aug 30

Chapter 3 (Describing data numerically)

Sept 8

Chapter 4 (Probability)

Sept 15

Chapter 5 (Discrete random variables and binomial distribution)

Sept 22

Chapter 6 (Continuous random variables and normal distribution)

Sept 29

Chapter 7 (Sampling distributions and confidence intervals for mean)

Oct 6

Chapter 8 (Sampling distributions and confidence intervals for proportion)

Oct 13

Chapter 9 (Hypothesis testing for one sample)

Oct 20

Chapter 10 (Hypothesis testing for two samples)

Oct 27

Chapter 11 (Correlation)

Nov 3

Chapter 12 (Regression)

Nov 10

Chapter 13 (Chi-square tests and goodness of fit)

Nov 17

Chapter 14 (ANOVA)

Nov 22

Review and Final Exam Prep

Dec 1

Final Exam (In class)

Key Course Components

Assessment and Grading

Student performance is evaluated through homework, quizzes, exams, and participation. The grading scale and point distribution are clearly outlined in the syllabus.

  • Homework: Regular assignments to reinforce concepts.

  • Quizzes: Short assessments to test understanding of recent material.

  • Exams: Major evaluations covering multiple chapters.

  • Participation: Engagement in class discussions and activities.

Assessment Type

Points

Percentage

Homework

100

10%

Quizzes

100

10%

Exams

600

60%

Final Project

200

20%

Course Policies and Resources

Academic Integrity and Conduct

The syllabus emphasizes the importance of academic honesty, proper use of technology, and respectful classroom behavior. Collaboration is allowed only when specified, and unauthorized sharing of work is prohibited.

  • Integrity: All submitted work must be original and adhere to university policies.

  • Technology: Use of personal laptops for exams; restrictions on unauthorized devices.

  • Attendance: Regular attendance and participation are expected.

Support and Accommodations

Students with disabilities or special needs are encouraged to contact the Center for Educational Access (CEA) for accommodations. Additional support is available through university resources and help desks.

Summary of Major Statistical Topics

Core Concepts in Business Statistics

  • Types of Data: Qualitative vs. quantitative, levels of measurement.

  • Descriptive Statistics: Summarizing data using tables, graphs, and numerical measures (mean, median, mode, standard deviation).

  • Probability: Basic rules, probability distributions, and their applications in business.

  • Random Variables: Discrete (e.g., binomial) and continuous (e.g., normal) distributions.

  • Sampling and Confidence Intervals: Estimating population parameters from samples.

  • Hypothesis Testing: Procedures for testing claims about means and proportions (one and two samples).

  • Correlation and Regression: Analyzing relationships between variables.

  • Chi-Square Tests: Assessing goodness of fit and independence in categorical data.

  • ANOVA: Comparing means across multiple groups.

Example: Confidence Interval for Mean

To estimate the population mean from a sample, use the confidence interval formula:

  • = sample mean

  • = critical value from standard normal distribution

  • = sample standard deviation

  • = sample size

Example: Hypothesis Testing for Proportion

To test a claim about a population proportion , use the test statistic:

  • = sample proportion

  • = hypothesized population proportion

  • = sample size

Additional info:

  • The syllabus provides a comprehensive outline matching the standard topics in a college-level Statistics for Business course.

  • Students are expected to use statistical software and online resources for assignments and exams.

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