7a. Prerequisite(s): (Course and/or other preparation/experience that is REQUIRED to be completed previous to enrollment in this course.)

Two years of high school algebra or Math. D with a grade of "C" or better, or placement by matriculation assessment process

7b. Co-requisite(s):  (Courses and/or other preparation that is REQUIRED to be taken concurrently with this course.)

7c. Advisory: (Minimum preparation RECOMMENDED in order to be successful in this course.  Also known as “Course Advisory”.)

9b. Catalog Description:

Introduction to the basic concepts of statistics. Emphasis on statistical reasoning and application of statistical methods. Areas included: graphical and numerical methods of descriptive statistics; basic elements of probability and sampling; binomial, normal, Student's t, and chi-square distributions; confidence intervals and hypothesis testing for one and two population means and proportions; chi-square tests for goodness-of-fit and independence; and linear regression and correlation. (CAN STAT 2)

10. Student Performance Outcomes: (Outcomes for all credit courses must indicate that students will learn critical thinking and will be able to apply concepts at college level.  Outcomes must be related to items listed in Section 11.)

Upon successful completion of this course, students will:
1. Identify the population and sample in a scenario where statistics is employed.
2. Identify the method of sampling utilized in a scenario where statistics is employed.
3. Classify a particular data item by type and level of measurement.
4. Operate a statistically enabled scientific calculator or computer software package to assist in the application of statistical methods.
5. Construct a distribution table, histogram, stem-and-leaf plot, Pareto chart, pie chart, and scatter diagram from raw data and describe the result.
6. Calculate the mean, median, and mode from raw data and interpret the result.
7. Calculate the standard deviation, coefficient of variation, and range from raw data and interpret the result.
8. Calculate the standard score of a data value and interpret the result.
9. Use the standard score to identify unusual data values.
10. Calculate the percentile of a data value and interpret the result.
11. Determine the data value for a particular percentile and interpret the result.
12. Use the basic rules of probability to calculate probabilities for simple and compound events.
13. Calculate conditional probabilities.
14. Use probabilities to determine if events are independent.
15. Construct a probability distribution for a discrete random variable and calculate the expected value.
16. Calculate probabilities based on the binomial probability distribution.
17. Calculate the mean and standard deviation of a binomial probability distribution.
18. Calculate probabilities based the normal probability distribution.
19. Apply the central limit theorem to determine probabilities concerning the mean of a sample.
20. Construct a confidence interval estimate for one population mean and interpret the result.
21. Construct a confidence interval estimate for one population proportion and interpret the result.
22. Conduct a hypothesis test involving one population mean and interpret the result.
23. Conduct a hypothesis test involving one population proportion and interpret the result.
24. Conduct a hypothesis test involving the difference between two population means and interpret the result.
25. Construct a confidence interval estimate for the difference between two population means and interpret the result.
26. Conduct a hypothesis test involving the difference between two population proportions and interpret the result.
27. Construct a confidence interval estimate for the difference between two population proportions and interpret the result.
28. Construct a confidence interval and conduct a hypothesis test with dependent paired samples and interpret the result.
29. Conduct a chi-square goodness-of-fit test and interpret the result.
30. Conduct a chi-square test for independence and interpret the result.
31. Calculate the linear correlation coefficient for a set of paired data and interpret the result.
32. Calculate the least squares regression line for a set of paired data and interpret the result.
33. Use the linear regression model when appropriate to make a prediction.

11. Course Content Outline: (Provides a comprehensive, sequential outline of the course content, including all major subject matter and the specific body of knowledge covered.)

1. Fundamental Statistical Concepts and Terms
a) Population, Census, and Sample
b) Methods of Sampling: Simple Random, Stratified, Cluster, and Systematic
c) Types of Data: Qualitative, Quantitative, Continuous, and Discrete
d) Levels of Measurement: Nominal, Ordinal, Interval, and Ratio
2. Descriptive Statistics
a) Graphical Methods: Distribution Table, Histogram, Stem-and-Leaf Plot, Pareto Chart, Pie Chart, and Scatter Diagram
b) Measures of Central Tendency: Mean, Median, and Mode
c) Measures of Dispersion: Standard Deviation, Coefficient of Variation, and Range
d) Measures of Position: Standard Scores and Percentiles
3. Introduction to Probability
a) Definition of Probability
b) Basic Rules of Probability
c) Conditional Probability and Independent Events
d) Random Variables, Probability Distributions, and Expected Values
e) Binomial Probability Distribution
f) Normal Probability Distribution
g) Central Limit Theorem
4. Inferential Statistics
a) Confidence Interval Estimate for One Population Mean
b) Confidence Interval Estimate for One Population Proportion
c) Hypothesis Testing Procedure and P-Values
d) Hypothesis Test Involving One Population Mean
e) Hypothesis Test Involving One Population Proportion
f) Hypothesis Test Involving Difference between Two Population Means
g) Confidence Interval Estimate of Difference between Two Population Means
h) Hypothesis Test Involving Difference between Two Population Proportions
i) Confidence Interval Estimate of Difference between Two Population Proportions
j) Confidence Interval and Hypothesis Test with Dependent Paired Samples
k) Chi-square Goodness-of-Fit Test
l) Chi-square Test for Independence
5. Introduction to Regression Analysis
a) Linear Regression Model
b) Linear Correlation Coefficient
c) Regression Model Predictions

12. Typical Assignments: (List types of assignments, including library assignments.)

a. Reading Assignments: (Submit at least 2 examples)

1. Read section of the textbook on standard scores.
2. Read section of the textbook on the binomial probability distribution.

b. Writing, Problem Solving or Performance: (Submit at least 2 examples)

1. A woman wrote to Dear Abby and claimed that she gave birth 308 days after a visit from her husband, who was in the Navy. Length of pregnancies have a mean of 268 days and a standard deviation of 15 days. Is such a length unusual? What do you conclude?
2. Air America has a policy of booking as many as 15 persons on an Airplane that can seat only 14. Past studies have revealed that only 85% of the booked passengers actually arrive for the flight. Find the probability that if Air America books 15 persons, not enough seats will be available. Is this probability low enough so that overbooking is not a real concern for passengers?

c. Other (Terms projects, research papers, portfolios, etc.)

SECTION D

SECTION E

SECTION F

SECTION G