Topic: Statistics

Order Description

1. Descriptive analysis

The analysis should include a summary of the data using appropriate charts and visual displays as well as descriptive statistics. Specifically, you should address the statistical differences among your variables. Critique your findings.

2. Regression Analysis

Play around with building various explanatory models for your dependent variable. Be sure to consult the correlation matrix when making a choice of variables to use, interpret all slopes/intercepts, evaluate the fit of your models, check whether model assumptions are verified, and, of course, use your model to make forecasts and give some idea of your confidence in your forecasts.

3. Overall Analysis

Critique the methods used in this project and offer suggestions for improvement or changes. Would you consider using those methods as a business person faced with uncertainty and needing to make decisions?

4. Report

First of all, you will submit a single report, no more than 10 pages long, and aimed at a general business audience. You may assume that your audience needs to make some decisions and is seeking a statistical perspective relatively free of technical jargon.

The document should be written in clear, concise, correct English. Just as with any formal writing assignment, mechanical mistakes and bad stylistic habits distract the reader from the points you’re trying to make.

How much output should you include in your report? Where should it go? Good questions. Here’s my best general advice: Focus on your own discussion and interpretation, and use the software’s plots and calculations primarily to back up your own claims and analysis. So at the very most, include output only if you discuss and analyze it in your text. Avoid abusing important jargon which has very precise technical meanings.

Where should you put the software’s results? Optimally you should import the relevant output into the appropriate spot of your document, just before or just after the discussion. Alternatively you may choose to put results in an Appendix. Regardless of where you include output, be sure to trim away all irrelevant detail, and include only what your reader really needs to see. Please remember to label all aspects of the plots appropriately.

Course syllabus is as follows:
Class
#
Lecture Topic
Chapter
Assessment Type &
Important Date
1
Introduction
– Role of statistics in management
– Presenting qualitative and quantitative data graphically
– Screening data: missing data and outliers, Normality, descriptive statistics
– Contingency tables, strength of association.
Chapters 3-4-5-6
Group assignment

Summarizing and presenting sales

transaction data: the case of

Expeditioner.

2
Regression Analysis
– Introduction to regression analysis
– Evaluating a model: slope, coefficients of determination and correlation
– Data transformations.

Chapters 19-20-21

Group assignment
Optimal pricing: How much should a retailer charge?

3
Introduction to Multiple Regression
– Understanding multicollinearity
– Building and interpreting models using categorical variables.

Chapters 23-34

Group assignment
Building a model to explain the level of business: the case of Hatco.

4
Introduction to Forecasting
– Qualitative and quantitative methods.
– Time series: components of time series.
– Incorporating trend and seasonality into models.
–
Chapter 27
Group assignment
Forecasting oil prices.

5
Building and using Decisions Models
– Model optimization and data fitting
– Models involving uncertainty: Monte Carlo simulations.

Materials will be
provided in class
Group assignment
The Newsvendor Model

Quiz

The data can be taken from any of the following:

https://www.opec.org/opec_web/en/data_graphs/40.htm
https://data.worldbank.org/
https://research.stlouisfed.org/

www.stats.gov.sa