This series of four Statistics courses plus a self-assessment covers the fundamentals of Descriptive Statistics. It is an overview for those who didn't understand Statistics in college or who have not had the opportunity to take a Statistics course. The series is also recommended for those who are working on a Six Sigma project and are collecting and analyzing data.

eLearning Modules Included:
- What is Statistics?
- Organization of Data
- Measures of Central Tendency
- Measures of Dispersion
- Descriptive Statistics: Self Assessment

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DESCRIPTIVE STATISTICS

What is Statistics?

- Given some basic terms used in statistics, students will be able to identify their definition.
- Student will be introduced to the basic terminology used in statistics.
- When given an example of a variable used in statistics, students will be able to classify the variable as quantitative or qualitative.
- Students will be given a scenario for collecting data and will be able to describe the difference between a population and a sample.
- An application for the use of statistics will be given to the students, and they will understand the difference between using descriptive and inferential statistics.

Organization of Data

- Students will be able to identify techniques for presenting the data in proper table or graphical format by using frequency table, bar graphs, Pareto charts, and pie charts.
- Graphical techniques for representing both Qualitative and Quantitative data will be examined.
- Frequency distributions, pie charts, bar graphs, Pareto charts, histograms, cumulative frequency distribution and stem-and-leaf plots will be introduced.
- Students will be able to interpret a graphical display of qualitative data and answer questions related to the interpretation of the data.
- From given qualitative data students will construct frequency tables, frequency distributions, histograms, cumulative frequency distributions, and stem- and-leaf plots.
- Interpret a graphical display of quantitative data and answer questions related to the interpretation.

Measures of Central Tendency

- Students will be able to calculate or identify the three measures of central tendency: mean, median and mode.
- In this course, the student will learn how to calculate some numerical measures of central tendency such as the mean, median and mode.
- Explore how measures of central tendency are affected by changes in the data.
- In a given histogram the student will be able to estimate the relationship of the median and the mean based upon the shape of the histogram.
- Within a set of data, students will be able to identify changes in the mean, median, and mode based upon a transformation made to the original data.
- Students will be able to calculate estimates for the median and mean also be able to identify the modal class when given a set of grouped data.

Measures of Dispersion

- Given a set of ungrouped data, students will be able to calculate or identify measures of dispersion such as the range and standard deviation.
- Measures such as the range, variance and standard deviation will be learned, as well as how to calculate them.
- Box-and-whisker plots will be introduced and interpreted.
- Students will be able to identify how a change in dispersion will affect the shape of the histogram.
- When given a set of data, students will be able to identify changes in the standard deviation based upon a transformation made to the original data.
- A data set will be shown to the students who will then be able to estimate percentage of measurements within a symmetrical interval about the mean.
- A mean and standard deviation will be given to the students who will then be able to calculate the Z score for a stated measurement.