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1-800-THE-TREE (1-800-843-8733)
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Introduction to Statistics: Making Better Business Decisions
Course: 196
Type: Hands-On Training
Duration: 3 Days
You Will Learn How To
- Bolster business decisions with proven statistical principles for interpreting and applying data
- Drive organizational results by administering probability-based tools
- Validate your data using appropriate statistical measures
- Leverage survey techniques to effectively evaluate data
- Prepare for future trend fluctuations through the use of forecasting
- Account for variability in your data results
Course Benefits In today's working environment, professionals face large volumes of data from which they must make informed and accurate decisions. This introductory course provides you with the statistical techniques to support your business decisions. By gathering and evaluating data using sound statistical methods, you learn to analyze and present information with clarity and precision.Who Should Attend Those who use data to support their business decisions, including anyone who manages quality, people, processes or any quantifiable resource. No prior knowledge of statistics or data analysis is assumed.Hands-On Training Exercises reinforce the statistical concepts and skills taught in class, including:
- Selecting the best chart for a business decision
- Applying decision trees and payoff tables effectively
- Leveraging descriptive statistics in business decisions
- Identifying differences between groups
- Designing and analyzing surveys
- Preparing and validating forecasts
- Analyzing summary data
Course 196 Content
- The need for sound data in the decision-making process
- Defining key statistical terminology
- Types of data: qualitative, quantitative
- Selecting the right charts to support decisions
- Three ways of estimating probabilities
- Combining probabilities for a stronger outcome
- Weighing the probabilities of related and unrelated events
- Blueprinting the decision tree architecture
- Applying expected values to determine the best decision
- Leveraging backward conditional probabilities to model a competitor's decision process
- Refining probabilities based on public information
- Interpreting data with statistical measures
- When to use the mean and other measures
- Exploring key measures of dispersion, such as standard deviation
- Quantifying skewness and kurtosis
- Detecting outliers
- Applying the Binomial Distribution to calculate the probability of success
- Finding the probability of defects by using the Poisson Distribution
- Selecting confidence intervals
- Estimating the mean and standard deviation
- Developing your hypothesis with tangible data
- Minimizing Type I and Type II errors
- Choosing one- or two-tailed tests
- Checking for equality of measures
- Performing measures of dispersion testing
- Discovering the sources of variability in your data
- Matching your data with a distribution
- Selecting the best test to apply
- Random
- Stratified
- Systematic
- Cluster
- Analyzing the required level of confidence
- Choosing the appropriate level of accuracy
- Focusing survey questions on key measures
- Selecting question types to pinpoint areas of concern
- Avoiding bias by ordering questions for accurate results
- Linear
- Exponential
- Logarithmic
- Calculating the coefficient of determination
- Measuring the "goodness of fit"
- Selecting the number of forecast periods
- Applying the trendline formula
- Analyzing your data to determine seasonality
- Applying seasonal factors to improve your forecast
- Data dredging
- Biased samples
- Communicating the main points
- Sidestepping common graphical mistakes
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