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Introduction to Statistics: Making Better Business Decisions

Course: 196   Type: Hands-On   Duration: 3 Days
Quick Enrol  

You Will Learn How To

  • Bolster business decisions with proven statistical principles for interpreting and applying data
  • Drive organisational 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 analyse 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 analysing surveys
  • Preparing and validating forecasts
  • Analysing summary data

Course Content
Introduction and Overview
  • 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
Assessing Probabilities
Fundamentals of probabilities
  • Three ways of estimating probabilities
  • Combining probabilities for a stronger outcome
  • Weighing the probabilities of related and unrelated events
Making decisions with decision trees
  • Blueprinting the decision tree architecture
  • Applying expected values to determine the best decision
Harnessing probabilities for competitive analysis
  • Leveraging backward conditional probabilities to model a competitor's decision process
  • Refining probabilities based on public information
Extracting and Validating Data
Exploiting effective measuring techniques
  • Interpreting data with statistical measures
  • When to use the mean and other measures
  • Exploring key measures of dispersion, such as standard deviation
Verifying distribution types
  • Quantifying skewness and kurtosis
  • Detecting outliers
Leveraging the power of distributions
  • Applying the Binomial Distribution to calculate the probability of success
  • Finding the probability of defects by using the Poisson Distribution
Applying Statistical Measures
Estimating population characteristics
  • Selecting confidence intervals
  • Estimating the mean and standard deviation
Testing hypotheses for future application
  • Developing your hypothesis with tangible data
  • Minimising Type I and Type II errors
  • Choosing one- or two-tailed tests
Comparing statistical measures between groups
  • Checking for equality of measures
  • Performing measures of dispersion testing
  • Discovering the sources of variability in your data
Obtaining substantive results through testing
  • Matching your data with a distribution
  • Selecting the best test to apply
Gathering Data Through Surveys
Applying probability-based sampling methods
  • Random
  • Stratified
  • Systematic
  • Cluster
Avoiding common mistakes in sampling
  • Convenience
  • Judgement
Selecting the right sample size
  • Analysing the required level of confidence
  • Choosing the appropriate level of accuracy
Creating your survey
  • Focusing survey questions on key measures
  • Selecting question types to pinpoint areas of concern
  • Avoiding bias by ordering questions for accurate results
Strengthening Your Forecasting Techniques
Incorporating the appropriate trend type
  • Linear
  • Exponential
  • Logarithmic
  • Calculating the coefficient of determination
  • Measuring the "goodness of fit"
Preparing your forecast
  • Selecting the number of forecast periods
  • Applying the trendline formula
Refining your forecast
  • Analysing your data to determine seasonality
  • Applying seasonal factors to improve your forecast
Identifying Misleading Statistical Techniques
Uncovering techniques used to mislead
  • Data dredging
  • Biased samples
Presenting data and conclusions accurately
  • Communicating the main points
  • Sidestepping common graphical mistakes
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Introduction to Statistics
Course Schedule
25 - 27 Jun, 2008
London
22 - 24 Oct, 2008
London
11 - 13 Feb, 2009
London

Participants interpreting data using standard deviation.

£ 1,395 - Standard Tuition
Savings Plans
£ 810 - 10-Day Training Pass
£ 995 - Flex-Training Passport
£ 800 - Short Course Vouchers
£ 1,255 - Alumni Gold Tuition

 
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Customer Service or Enrol: 0800 282 353 or +44 1372 364610