STATISTICS: Western University

Description

“An introductory course in the application of statistical methods, intended for honors students in departments other than Statistical and Actuarial Sciences, Applied Mathematics, Mathematics, or students in the Faculty of Engineering. Topics include sampling, confidence intervals, analysis of variance, regression and correlation. Cannot be taken for credit in any module in Statistics, Actuarial Science, or Financial Modeling.”

Sections

Description

“Descriptive statistics and graphs, probability and distributions. Sampling, hypothesis testing, and confidence intervals. Experimental design and analysis of variance. Regression and correlation, including multiple regression. Applications emphasized. This course cannot be taken for credit in any module in Statistics, Actuarial Science, or Financial Modelling.”

Sections

• 1 Introduction to Statistics
• 2 Charts and Graphs
• 3 Descriptive Statistics
• 4 Probability
• 5 Discrete Distributions
• 6 Continuous Distributions
• 7 Sampling and Sampling Distributions
• 8 Statistical Inference: Estimation for Single Populations
• 9 Statistical Inference: Hypothesis Testing for Single Population
• 10 Statistical Inferences about Two Population
• 11 Analysis of Variance and Design of Experiments
• 12 Correlation and Simple Regression Analysis
• 13 Multiple Regression Analysis
• 16 Analysis of Categorical Data

Description

“An introduction to econometric description and inference which covers: descriptive statistics for cross-section and time-series samples, probability; probability distributions and random variables; estimators and sampling distributions; confidence intervals and tests of hypotheses; simple linear regression.”

Sections

• 1 Introduction to Statistics
• 2 Measures of Central Tendency & Dispersion
• 3 Probability Theory
• 4 Discrete Probability Distributions
• 5 Continuous Probability Distribution
• 6 Sampling Distributions
• 7 Estimation -- Point and Interval
• 8 Hypothesis Testing
• 9 Introduction to Simple Linear Regression

Description

“An introduction to econometric description and inference which covers: descriptive statistics for cross-section and time-series samples; probability, discrete and continuous probability distributions, random variables; estimators and sampling distributions; confidence intervals and tests of hypotheses; simple linear regression for normal and non-normal populations. ”

Sections

• 1 Introduction
• 2 Descriptive Statistics
• 3 Probability Theory
• 4 Discrete Probability Distribution
• 5 Continuous Probability Distribution
• 6 Sampling Distributions
• 7 Point Estimation and Confidence Intervals
• 9 Hypothesis Testing
• 11 Linear Regression
• 10 Hypothesis Testing III (Wilcoxon, Matched, Dependent, and Repeated Measures)
• 11 Hypothesis Testing IV (ANOVA)
• 12 Hypothesis Testing V (Regression & Chi Square)

Description

“Introduction to data analysis with particular reference to statistical procedures commonly used in Psychological research.”

Sections

• 1 Introduction and Descriptive Statistics I
• 2 Descriptive Statistics II
• 3 Probability I
• 4 Probability II (Counting Rules)
• 5 Discrete Random Variables (Binomial Distribution)
• 6 Continuous Random Variables
• 7 Introduction to Inferential Statistics (Sampling Distribution)
• 8 Hypothesis Testing I (Large Sample)
• 9 Hypothesis Testing II (Two Means)
• 10 Hypothesis Testing III (Wilcoxon, Matched, Dependent, and Repeated Measures)
• 11 Hypothesis Testing IV (ANOVA)
• 12 Hypothesis Testing V (Regression & Chi Square)

Description

“An introduction to the design, conduct, and statistical analyses of psychological research. The intent is to provide students with knowledge of how to implement and evaluate research in both laboratory and applied settings. Design and statistical analysis will be taught in the context of specific studies and data sets from correlational, experimental, quasi-experimental and qualitative research. Written research projects will be required.”

Sections

Description

“An advanced treatment of the collection, analysis and interpretation of behavioral data, reviewing and extending the topics covered in Psychology 1100E; problems in the design and conduct of studies and experiments, operational definitions, experimental control and recording of behavior; statistical treatment of data, including descriptive and inferential statistics.”

Sections

Description

“This course provides an introduction to techniques of statistical analysis with an emphasis an application in Psychology. Topics include descriptive statistics, the normal distribution, probability, inferential statistics, and hypothesis testing. Also included will be discussion on the interpretation of statistics in other research designs including correlation, repeated samples testing and analysis of variance.”

Sections

Description

“This course covers most statistical procedures used in psychological research, and the use and interpretation of SPSS for Windows. Topics covered include the t-test, various forms of analysis of variance, chi-square, bivariate and multiple regression and correlation, factor analysis, and Monte Carlo methods.”

Sections

• 1 Introduction
• 2 The t-test
• 3 Monte Carlo methods; power; Type I error
• 4 Single factor analysis of variance designs
• 5 CRF designs; post hoc tests
• 6 Single factor repeated measures
• 7 Split plot analysis of variance
• 8 Chi-Square analysis
• 9 Bivariate correlation and regression
• 10 Multiple correlation and regression
• 11 Factor analysis

Description

“This is an introductory course to Statistical analysis, through which you will learn basic quantitative techniques used by social scientists. These include descriptive statistics, the normal curve, hypothesis testing and various measures of association. Students will learn to calculate statistics by hand and by using statistical software. While this course does not require a high level of math ability, it is expected that the students understand basic mathematical operations, and that they can operate a calculator. A pocket calculator that has a square root function (and preferably a memory) is required for this course. ”

Sections

• 1 Introduction
• 2 Basic Descriptive Statistics: Percentages, Ratios and Rates, Frequency Distributions
• 3 Charts and Graphs
• 4 Measures of Central Tendency
• 5 Measures of Dispersion
• 6 The Normal Curve
• 7 Introduction to Inferential Statistics, the Sampling Distribution, and Estimation
• 8 Hypothesis Testing I: The One-Sample Case
• 9 Hypothesis Testing II: The Two-Sample Case
• 10 Hypothesis Testing III:The Analysis of Variance
• 11 Hypothesis Testing IV: Chi Square
• 12 Introduction to Bivariate Association and Measures of Association for Variables Measured at the Nominal Level
• 13 Association Between Variables at the Ordinal Level
• 14 Association Between Variables Measured at the Interval-Ratio Level

Description

“The purpose of this course is to introduce students to quantitative decision-making skills, with an emphasis on analysis techniques used in management. Topics include: descriptive statistics, probability, hypothesis testing, analysis of variance, correlation and regression, time series forecasting, and survey techniques. ”

Sections

• 1 Introduction to Business Statistics
• 2 Descriptive Statistics
• 3 Probability
• 4 Discrete Random Variables
• 5 Continuous Random Variables
• 6 Sampling Distributions
• 8 Hypothesis Testing
• 9 Statistical Inferences Based on Two Samples
• 7 Confidence Intervals
• 14 Chi-Square Tests
• 10 Experimental Design and Analysis of Variance
• 11 Correlation Coefficient and Simple Linear Regression Analysis
• 12 Multiple Regression
• 16 Time Series Forecasting

Description

“The purpose of this course is to introduce students to quantitative decision-making skills, with an emphasis on analysis techniques used in management. Topics include: descriptive statistics, probability, hypothesis testing, analysis of variance, correlation and regression, time series forecasting, and survey techniques. ”

Sections

• 1 Introduction
• 2 Formulating a Research Problem
• 3 Research Design
• 4 Data Collection, Sampling, Data
• 5 Displaying and Interpreting Data
• 6 Describing Data with Statistics
• 7 Random Variables and Probability Distributions
• 8 Hypothesis Testing
• 9 Analysis of Variance
• 10 Correlation and Linear Regression