Syllabus

STA 2122: INTRODUCTION TO STATISTICS I

Revised July 31, 2008

Prerequisite:   High School Algebra

Terms Offered: Fall, Spring and Summer

Text:  Statistics, FIU custom edition, by James McClave and Terry Sincich

1. Statistics, Data, and Statistical Thinking? (Chapter 1)

Discuss the basic concepts of Statistics: data, population, sample, parameter, and statistic. Discuss the role of statistics in the scientific method. Explain the goal of statistics. Discuss types of data, data collection and the role of statistics in critical thinking.

2. Methods for Describing Sets of Data (Chapter 2: Sections 2.1-2.7; 2.8 optional, and 2.10 (read only))

Discuss graphical methods for qualitative and quantitative data, measures of central tendency, measures of variability, interpreting the standard deviation, and  measures of relative standing.

3. Probability (Chapter 3: Sections 3.1-3.7)

Discuss the basic concepts in probability: experiment, sample space, simple event, event, complement of an event, union and intersections of events, probability of an event, conditional probabilities, independent events, mutually exclusive events and Venn diagrams. Introduce random sampling.

4. Discrete Random Variables (Chapter 4: Sections 4.1-4.4)

Define random variable. Introduce the types of random variable. Introduce probability distributions for discrete random variables. Compute the mean and variance of a discrete random variable. Give the characteristics of a binomial random variable, and use the binomial tables to find the probability for possible outcomes of a binomial experiment.

5. Continuous Random Variables (Chapter 5: Sections 5.1 and 5.3)

Introduce probability distributions for continuous random variables with emphasis on the normal distribution. Use the standard normal table to find probabilities.

6. Sampling Distributions (Chapter 6: Sections 6.1-6.3)

Define sampling distribution of a sample statistic, and list the desired properties of a good estimator. Introduce the sampling distribution of the sample mean from a normal distribution. State the Central Limit Theorem in terms of the sampling distribution of the sample mean. Use the standard normal table to find probabilities associated with the sample mean.

7. Inferences Based on A Single Sample: Estimation (Chapter 7:Sections 7.1-7.4)

Define confidence interval. Compute confidence intervals for µ based on both large and small samples and confidence intervals for the binomial parameter, p, for large samples.

8. Inferences Based on A Single Sample: Tests of Hypotheses (Chapter 8: Sections 8.1-8.5)

Discuss the elements of a test of hypothesis. Define Type I and Type II errors. Perform tests of hypotheses about µ and p based on large samples and about µ based on small samples. Define the observed significance level of the test statistic, p-value.