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The Basic Statistics topic will provide the participant with the knowledge and skills necessary to statistically characterize virtually any set or array of data. This topic represents the first step into the world of applied statistics, and therefore the underpinning principles and practices contained within are vital to realizing a higher level of analytical power. Students will organize a set of data for subsequent statistical analysis using descriptive statistics and match that data to a common distribution such as the normal curve. In addition, candidates will learn how to define the central value of that data distribution, characterize the inherent variability associated with that distribution and estimate the probability of any given value or point of interest. Participants will then be taught how to report the related statistics and descriptive findings in a simple and comprehensible manner.
Of course, such knowledge and skills are essential for the successful execution of process capability studies and product characterization efforts. Furthermore, this topic will prepare a participant to undertake the study and application of such tools as Applied Diagnostic Methods (ADM), Statistical Process Control (SPC) and Design of Experiments (DOE). In this context, it is easy to see why Basic Statistics is the backbone of so many modern process improvement tools, methods and practices. For all intents and purposes, this topic is essential to the career development goals of anyone involved in the field of business improvement.
Reinforcement of major concepts, techniques, and application is realized through exercises, scenarios, and case studies. Total instructional time for this topic is 9 hours and 6 minutes.
- Performance Variables - Identify and describe the types of variables typically encountered in field work
- Statistical Notation - Recognize and interpret the conventional forms of statistical notation
- Performance Variation - Explain the basic nature of variation and how it can adversely impact quality
- Normal Distribution - Describe the features and properties that are characteristic of a normal distribution
- Distribution Analysis - Explain how to test the assumption that a set of data is normally distributed
- Location Indices - Identify, compute, and interpret the mean, median, and mode
- Dispersion Indices - Identify, compute, and interpret the range, variance, and standard deviation
- Quadratic Deviations - Understand the nature of a quadratic deviation and its basic purpose
- Variation Coefficient - Compute and interpret the coefficient of variation
- Deviation Freedom - Explain the concept of degrees-of-freedom and how it is used in statistical work
- Standard Transform - Describe how to transform a set of raw data into standard normal deviates
- Standard Z-Probability - Describe how to convert a standard normal deviate into its corresponding probability
- Central Limit - Understand that the distribution of sampling averages follows a normal distribution
- Standard Error - Recognize that the dispersion of sampling averages is described by the standard error
- Student's Distribution - Understand that the T distribution applies when sampling is less than infinite
- Standard T-Probability - Describe how to convert a T value into its corresponding probability
- Statistics Simulation - Employ basic statistics to analyze data generated by the process simulator