STAT 101:  INTRODUCTION TO STATISTICS

 

 

COURSE TOPICS

 

Statistical topics will be selected from, but are not limited to the following areas.  Some topics may not be covered.

 

 

Introduction to Statistics:   Aim of Statistics.  Basic definitions.  Why statistics is important to you.  Abuses of statistics.  Steps in scientific research.

 

Survey Sampling:  What is sampling?  Why do we sample?  Various sampling techniques.

 

Statistical Software:  Instruction in the fundamentals of using Minitab for statistical analysis.

 

Design of Experiments:  What is an experiment?  Identification of the components of an experiment.  Diagramming an experiment. Types of experiments.

 

Describing Data:  Using a variety of tables and graphs to describe data.

 

Measures of Central Tendency:  Determining the numerical characteristics of a data set.

 

Measures of Variation:  What is variance?  What is standard deviation?  The Empirical Rule.

 

Measures of Position:  Quartiles; Five-Number Summary; Boxplots.

 

Descriptive Methods in Regression and Correlation:  Linear equations; Linear regression with one independent variable; Scatterplots; Method of Least Squares; Coefficient of Determination; Linear correlation.

 

Elementary Probability:  Rules and applications of basic probability.

 

Probability Distributions:  Distribution of a random variable.

 

The Standard Normal Distribution:  What makes the Standard Normal Distribution a special distribution?  Use of the Standard Normal Table.  Z-scores.  Finding areas under the Standard Normal curve.

 

Nonstandard Normal Distributions:  What is a nonstandard normal distribution?  How to find probabilities given a nonstandard normal distribution.

 

Sampling Distributions:  What are they?  The Central Limit Theorem.

 

Confidence Intervals:  Estimating a population mean.

 

Hypothesis Tests:  For a population mean.  What are hypothesis tests?  Types of errors.  P-value.

 

Population Proportions:  Difference between a population proportion and a sample proportion.  Confidence intervals and hypothesis tests for population proportions.

 

Chi-Square:  Goodness of Fit Test; Test for Independence.

 

t-test:  One-sample; Independent Samples; Paired Samples.

 

f:Stat101 Course Topics.doc