Course Objectives:

1.         Identify, develop, and solve statistical problems related to real world situations.
2.         Identify, and use statistical problem-solving strategies.
3.         Interpret tabular and graphical data to solve statistical problems.
4.         Manipulate statistical items numerically, symbolically, graphically and in writing.
5.         Use technology appropriately in problem solving and in exploring and developing statistical concepts.
 

Topical Outline:

1.         Statistical terms such as: population, sample, or (response) variable, data types, or descriptive and inferential statistics.
2.         Identify sampling techniques.
3.         Frequency distributions from raw data. 
4.         Interpret data in graphical form such as a histogram, stem-and-leaf plot, or box-and-whisker plot.
5.         Describe data by measures of center, variation (dispersion) of position.
6.         Learn terms related to probability such as: experiments, outcomes, sample space, or event.
7.         Rules of probability.
8.         Probability distribution for discrete random variables.
9.         Compute the mean (expected value), variance, or standard deviation of a discrete probability distribution.
10.       Computations for a special discrete probability distribution such as: binomial, hyper geometric, multinomial, or Poisson.
11.       Demonstrate knowledge of the properties for a normal or standard normal distribution.
12.       Area under the normal curve.
13.       Application problem involving the normal distribution.
14.       Demonstrate knowledge of the Central Limit Theorem.
15.       Solve an application problem involving the Central Limit Theorem.
16.       Demonstrate knowledge of terms related to interval estimation such as: point estimate, confidence interval, or confidence level, maximum error of estimate (margin of error), or critical value.
17.       Compute a confidence interval or sample size needed for the population mean or population proportion.
18.       Interpret a confidence interval for the population mean or population proportion.
19.       Learn terms related to hypothesis testing such as: null and alternative hypotheses, significance level, or rejection (critical) region, types of statistical tests, test statistic (test value), type I and II errors, or p-value.
20.       Perform or state a hypothesis test for the population mean or population proportion.