MAT 203 Principles of Statistics

Weiss, Neil, Introductory Statistics 9th Edition 2016, published by Pearson
ISBN-13: 978-0321989406
ISBN-10: 0321989406

1) Students can obtain this text book from the following source:
http://www.mypearsonstore.com/bookstore/introductory-statistics-plus-mystatlab-with-pearson-9780321989406

All reading and (optional) homework assignments referenced in this syllabus refer to this text

2) In addition, it is recommended that students have access to MyStatLab®, by Pearson. This can be accessed here:
http://www.mypearsonstore.com/bookstore/mystatlab-with-pearson-etext-instant-access-for-introductory-0321989341

3) The following study guide will be made available upon enrollment:
Weiss, Neil, PowerPoint Presentation for Introductory Statistics 9th Edition  2016, published by Pearson

Lesson Overview

Lesson 1: The Nature of Statistics
Read Chapter 1

In this lesson, the students are introduced fundamental basics of statistics basics.  The students learn about simple random sampling and other sampling designs.  The students look at experimental designs and data analysis using case studies from the film industry.

Lesson 2: Organizing data
Read Chapter 2

In this lesson, the students learn about organizing variables and data in terms of both qualitative data and quantitative data.  The students look at different distribution shapes and learn how to recognize misleading graphs.  The students have a case study discussion of, “The World’s Richest People.”

Lesson 3: Descriptive Measures
Read Chapter 3

In this lesson, the students learn about the measures of center and the measures of variation.  The students learn about Chebyshev’s rule and the empirical rule.  The students look at the five-number summary and learn about boxplots.  The students examine descriptive measures for populations and the use of samples.

Lesson 4: Probability Concepts
Read Chapter 4

In this lesson, the students are introduced to the basics of probability.  The students learn about the idea of “events” and explore some of the rules of probability.  The students look at contingency tables with respect to joint and marginal probabilities.  The students learn about conditional probability, the multiplication rule, and independence.  The students look at Bayes’s rule and other counting rules.

Lesson 5: Discrete Random Variables
Read Chapter 5

In this lesson, the students learn about discrete random variables and probability distributions.  The students look at the mean and standard deviation of a discrete random variable.  The students learn about the binomial distribution and the Poisson distribution.

Lesson 6: The Normal Distribution
Read Chapter 6

In this lesson, the students are introduced to normally distributed variables and look at the areas under the standard normal curve.  The students learn about working with normally distributed variables and assessing normality.  The students look at normal probability plots and learn about how to make a normal approximation to the binomial distribution.

Lesson 7: The Sampling Distribution of the Sample Mean
Read Chapter 7

In this lesson, the students learn about sampling error and the need for sampling distributions.  The students look at the mean and standard deviation of the sample mean.  The students learn about the implication of the sample mean with respect to the sampling distribution.

Lesson 8: Confidence Intervals for One Population Mean
Read Chapter 8

In this lesson, the students learn about estimating a population mean.  The students examine confidence intervals for one population mean for when σ is known and for when σ is unknown.

Lesson 9: Hypothesis Tests for One Population Mean

Read Chapter 9

In this lesson, the students learn about the nature of hypothesis testing with respect to the critical-value approach to hypothesis testing and to the p-value approach to hypothesis testing.  The students learn about hypothesis tests for one population mean when σ is known and for when σ is unknown.  The students look at the Wilcoxon signed-rank test and learn about Type II error probabilities.  The students learn about the idea of power and examine when each procedure should be used.

Lesson 10: Inferences for Two Population Means

Read Chapter 10
In this lesson, the students look at the sampling distribution of the difference between two sample means for independent samples.  The students make inferences for two population means, using independent samples when standard deviations assumed equal and for when standard deviations not assumed equal.  The students look at the Mann–Whitney test and make inferences for two population means, using paired samples.  The students look at the paired Wilcoxon signed-rank test and learn about when each procedure should be used.

Lesson 11: Inferences for Population Standard Deviations
Read Chapter 11

In this lesson, the students learn about inferences for one population standard deviation and inferences for two population standard deviations.  The students learn about the implications of using independent samples.

Lesson 12: Inferences for Population Proportions

Read Chapter 12
In this lesson, the students learn about confidence intervals for one population proportion and how make hypothesis tests for one population proportion.  The students also learn about making inferences for two population proportions.

Lesson 13: Chi-Square Procedures
Read Chapter 13

In this lesson, the students are introduced to the chi-square distribution and the chi-square goodness-of-fit test.  The students look at contingency tables with respect to association.  The students learn how to make a chi-square independence test and a chi-square homogeneity test.
Lesson 14:  Descriptive Methods in Regression and Correlation
Read Chapter 14

In this lesson, the students review how to work with linear equations with one independent variable.  The students learn about the regression equation and how to interpret the coefficient of determination.  The students learn about the concept of linear correlation.

Lesson 15: Inferential Methods in Regression and Correlation
Read Chapter 15
In this lesson, the students look at the regression model and analysis of residuals.  The students learn about the inferences for the slope of the population regression line and how to make estimations and predictions.  The students learn about inferences in correlation and their limitations.
Lesson 16: Analysis Of Variance (ANOVA)
Read Chapter 16
In this lesson, the students learn about the F-distribution and the one-way ANOVA with respect to its logic and procedure.  The students learn how to make multiple comparisons and learn about the Kruskal–Wallis test.
Lesson 17: Multiple Regression And Model Building; Experimental Design And ANOVA
Read Modules A, B, and C

Module A: Multiple Regression Analysis
In this module, the students review the multiple linear regression model and the estimation of the regression parameters.  The students make inferences concerning the utility of the regression model and concerning the utility of particular predictor variables.  The students review how to find the confidence intervals and prediction intervals for mean response.  The students learn how to check model assumptions and make residual analysis.

Module B: Model Building in Regression
In this module, the students learn how to make transformations to remedy model violations.  The students look at the polynomial regression model and learn about qualitative predictors and multicollinearity.  The students learn about stepwise regression and all-subsets regression.  The students learn about the limitations of model building in regression.

Module C: Design of Experiments And Analysis Of Variance
In this module, the students learn about factorial designs.  The students look at the logic and procedure of two-way ANOVA with respect to multiple comparisons.  The students learn about randomized block designs and learn about the logic and procedure of randomized block ANOVA with respect to making multiple comparisons.  The students look at Friedman’s nonparametric test for the randomized block design.

The student’s final grade will be based on a final examination. Examination questions will cover all topics covered in the readings. Students will have two hours to complete the final examination.  Students will be assigned a number grade from 0-100. A letter grade will also be issued in accordance with the following scale:

90-100 – A
80-89 – B
70-79 – C
0-69 – non passing