# Stat 1040 Course Objectives

Course Goals:

A student will be able to:

1. Interpret mathematical information using symbolic, visual, numerical and verbal conventions.
2. Solve problems using numeric, algebraic, geometric and statistical method.
3. Use quantitative information in context to determine reasonableness of results.
4. Use appropriate mathematical tools (e.g. calculators, computers, measurement instruments and manipulatives) in problem solving.

Description

A quantitative literacy course with a statistical theme. Includes descriptive statistics, sampling, and inferential methods. Emphasizes problem solving and critical thinking.

Design of Experiments

A student is able to:

1. Distinguish between observational studies and randomized comparative experiments.
2. Explain the logic of experimental design including the concepts of blinding and the placebo effect.
3. Identify confounding and discuss “control” as it relates to both experiments and observational studies

Descriptive Statistics

A student is able to:

1. Accurately read and interpret density histograms
1. Compute percent of observations above or below a given value using area under the curve.
2. Estimate the average and standard deviation of the distribution.
3. Describe shape of the distribution.
2. Compute the average and standard deviation for numerical data sets
3. Compute the five number summary, construct and accurately interpret boxplots.
4. Compute percentiles and probabilities for the normal distribution using both the z-transformation and the “68-95-99.7” rule
5. Separate measurement error into chance error and bias.

Correlation and Regression

A student is able to:

1. Determine strength and direction of the relationship between two variables using a scatter plot.
2. Estimate the correlation from a scatter plot.
3. Compute the correlation coefficient..
4. Distinguish between association and causation and discuss the limitations of correlation.
5. Distinguish between studies using cross-sectional data versus longitudinal data and discuss their ramifications.
6. Compute and make predictions using the standard deviation line.
7. Compute and make predictions using the regression line.
8. Compare the standard deviation line to the regression line and discuss the regression to the mean phenomena.
9. Compute and interpret the root mean square error for regression.
10. Compute and interpret the coefficient of determination for regression.
11. Compute probabilities using the normal curve inside a vertical strip in regression.

Probability

A student is able to:

1. Compute probabilities using the multiplication rule.
2. Distinguish between conditional probabilities and independence.
3. Compute probabilities using the addition rule.
4. Identify mutually exclusive events.

Chance Variability

A student is able to:

1. Discuss the Law of Averages.
2. Compute absolute error and relative error for a chance process.
3. Compute the expected value and standard error for the sum / avg. of draws in a chance process.
1. Numerical data
2. Count / classify data
4. Use the normal curve to compute probabilities for the sum / avg. of draws in a chance process.
1. Numerical data
2. Count / classify data

Sampling

A student is able to:

1. Compare and contrast probability sampling methods with quota sampling methods.
2. Distinguish between populations and samples.
3. Identify target population and sample population.
4. Distinguish between parameters and statistics.
5. Identify types of bias in sampling: selection bias, non-response bias, response bias.
6. Compute and interpret confidence intervals for the population average.
7. Compute and interpret confidence intervals for the population proportion / percent.

Tests of Significance

A student is able to:

1. Conduct a large sample test of significance for the population average
2. Conduct a small sample test of significance for the population average.
3. Conduct a large sample test of significance for the population proportion / percent.
4. Conduct a test of significance to compare two population averages using independent samples
5. Conduct a test of significance to compare two population proportions / percents using independent samples.
6. Conduct the chi-square goodness-of-fit test.
7. Conduct the chi-square test for independence.
8. Interpret p-values and statistical significance.
9. Discuss the limitations of tests of significance.

Practice Questions

Chapter 1/2Chapter 3, Chapter 4, Chapter 5/6, Chapter 8Chapter 9, Chapter 10Chapter 11Chapter 12Chapter 13Chapter 14, Chapter 16, Chapter 17Chapter 18Chapter 19Chapter 20Chapter 21Chapter 23Chapter 26Chapter 27Chapter 28Chapter 29.