Introduction to Statistics for Data Science

Level: Intermediate

This hands-on introduction to statistics for data science gives you the tools required to make sense of data and draw *valid* conclusions. The focus of this course is on statistical thinking. Concepts will be introduced intuitively before being expanded formally. You will learn how to think in terms of distributions---not single point estimates. Statistical tools will be introduced in the context of how to use them to gain insight and solve problems. You will also learn how to use the powerful, industry-standard R environment to do the number-crunching in this statistics for data science course.

Key Features of Introduction to Statistics for Data Science:

  • Learning Tree end-of-course exam included
  • After-course computing sandbox included
  • After-course instructor coaching included

You Will Learn How To:

  • Visualize data
  • Draw conclusions about the features and quality of data sets
  • Summarize your data
  • Think of numbers as distributions
  • Use the power of computers to generate distributions for any problem
  • Determine correlation---and move from there to demonstrating causation
  • Make valid statistic inferences using a range of hypothesis tests
  • Obtain accurate random samples
  • Use regression to predict the value of one variable based on others
  • Design and execute your own statistical projects

Choose the Training Solution That Best Fits Your Individual Needs or Organizational Goals

LIVE, INSTRUCTOR-LED

In Class & Live, Online Training

  • 2-day instructor led training course
  • After-course computing sandbox included
  • After-course instructor coaching included
  • Tuition fee can be paid later by invoice -OR- at the time of checkout by credit card
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Standard $2225

Government $1950

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  • Blended learning models
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  • Expert team coaching

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In Class & Live, Online Training

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Note: This course runs for 2 Days

  • Jun 15 - 16 9:00 AM - 4:30 PM EDT Herndon, VA / Online (AnyWare) Herndon, VA / Online (AnyWare) Reserve Your Seat

  • Jul 13 - 14 9:00 AM - 4:30 PM EDT New York / Online (AnyWare) New York / Online (AnyWare) Reserve Your Seat

  • Aug 10 - 11 9:00 AM - 4:30 PM EDT Ottawa / Online (AnyWare) Ottawa / Online (AnyWare) Reserve Your Seat

  • Sep 14 - 15 9:00 AM - 4:30 PM EDT Herndon, VA / Online (AnyWare) Herndon, VA / Online (AnyWare) Reserve Your Seat

  • Oct 13 - 14 9:00 AM - 4:30 PM EDT New York / Online (AnyWare) New York / Online (AnyWare) Reserve Your Seat

  • Nov 9 - 10 9:00 AM - 4:30 PM EST Ottawa / Online (AnyWare) Ottawa / Online (AnyWare) Reserve Your Seat

  • Dec 14 - 15 9:00 AM - 4:30 PM EST Herndon, VA / Online (AnyWare) Herndon, VA / Online (AnyWare) Reserve Your Seat

  • Jan 11 - 12 9:00 AM - 4:30 PM EST New York / Online (AnyWare) New York / Online (AnyWare) Reserve Your Seat

  • Feb 8 - 9 9:00 AM - 4:30 PM EST Ottawa / Online (AnyWare) Ottawa / Online (AnyWare) Reserve Your Seat

  • Mar 15 - 16 9:00 AM - 4:30 PM EDT Herndon, VA / Online (AnyWare) Herndon, VA / Online (AnyWare) Reserve Your Seat

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Important Statistics for Data Science Course Information

  • Requirements

    There are no formal prerequisites for attending this course.

Statistics for Data Science Course Outline

  • Why is statistics important?

    • Make valid recommendations
    • Avoid basic data analysis errors
    • Assess dubious claims
    • Formalize intuition
  • Visualizing data

    • Types of data
    • Histograms
    • Skewed data
    • Subpopulations
    • Outliers
    • Effect of sample size
    • Individual value plots
    • Box plots
    • Scatter plots
    • Two-way contingency tables
    • Lying with charts
  • Summary statistics

    • Measures of central tendency
    • Measures of dispersion
    • Percentiles
    • Correlation
    • Correlation vs causation
  • Probability distributions

    • What *is* a probability distribution?
    • Monte Carlo methods
    • Discrete probability distributions
    • Binomial distribution
    • Continuous probability distributions
    • Normal distribution
    • Z-scores
    • Poisson distribution
  • Inferential statistics

    • Descriptive vs inferential statistics
    • Samples vs populations
    • Statistics vs parameters
    • Sampling the mean
    • Confidence intervals
    • Sample size and margin of error
    • Random sampling
  • Hypothesis testing

    • What test should I use?
    • p-values
    • z-test
    • t-test
    • ANOVA
    • Chi-square test
    • Statistical power
  • Regression

    • Simple linear regression
    • Multiple regression
    • Hypothesis tests of regression coefficients
  • Conducting experiments

    • Determining causation
    • Confounding variables
    • Randomized experiments
    • Natural experiments
    • Observational studies
    • Evaluating experiments

Team Training

Statistics for Data Science FAQs

  • What is statistics?

    Statistics is the science of analyzing data, particularly in large quantities, and using it to draw more general conclusions.

  • Why is a knowledge of statistics valuable in business?

    Without statistics, conclusions drawn from data can be fatally flawed. As data becomes ubiquitous, the ability to analyze it responsibly is essential.

  • What background do I need for this Statistics for Data Science Course?

    Participants be able to understand basic mathematical concepts (high-school level) and have a level of comfort with using computer software, such as Excel.

  • Does this include any practical, hands-on learning?

    Yes. There are various opportunities to conduct analyses throughout the period of the training.

  • Can I take this training course online?

    Yes! We know your busy work schedule may prevent you from getting to one of our classrooms which is why we offer convenient online training to meet your needs wherever you want. This course is available online, in person, or as Private Team Training.

Herndon, VA / Online (AnyWare)
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Herndon, VA / Online (AnyWare)
New York / Online (AnyWare)
Ottawa / Online (AnyWare)
Herndon, VA / Online (AnyWare)
New York / Online (AnyWare)
Ottawa / Online (AnyWare)
Herndon, VA / Online (AnyWare)
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