Statistics 1 – Probability and Study Design

This course, the first of a three-course sequence, provides an introduction to statistics for those with little or no prior exposure to basic probability and statistics.

This course, the first of a three-course sequence, provides an introduction to statistics for those with little or no prior exposure to basic probability and statistics.

$489 | Enroll Now
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Overview

This course, the first of a three-course sequence, provides an introduction to statistics for those with little or no prior exposure to basic probability and statistics. Once you have completed this course you will be able to apply statistically valid designs to basic studies, and test hypotheses regarding proportions and means.

Introductory Level Course
4-Week Course
100% Online Courses
ACE + CAP Credit Eligible
ACE + CAP Credit Eligible
Expert Instructors
Teacher Assistant Support
Tution-Back Guarantee

Learning Outcomes

After completing this course you will understand the fundamental basis for statistical inference. Topics covered include probability, the Normal distribution, hypothesis testing, independence, conditional probability, Bayes Rule, 2-way tables, random sampling, and confidence intervals.

  • Appropriately calculate various measures of location and variability
  • Produce histograms, boxplots and other visual displays
  • Explain what the null hypothesis is
  • Use resampling methods to test a null hypothesis and calculate a p-value
  • Index time series data
  • Calculate probabilities (conditional and unconditional)
  • Apply Bayes Rule
  • Specify a random sampling protocol
  • Conduct bootstrap sampling
  • Assess survey results
  • Determine confidence intervals

Who Should Take This Course

Anyone with no prior statistical background, who encounter statistics in their work, or who needs introductory statistics for further study.

Instructors

Mr. Peter Bruce

Mr. Peter Bruce

Mr. Peter Bruce is Founder and President of The Institute for Statistics Education at Statistics.com. He is the developer of Resampling Stats software (originated by Julian Simon in the 1970's), and has also taught resampling statistics at the University of Maryland and in a variety of short courses. He is the author of Responsible Data Science, with Grant Fleming (Wiley, 2021), Machine Learning for Business Analytics, with Galit Shmueli, Peter Gedeck, Inbal Yahav and Nitin R. Patel (prior title Data Mining for Business Analytics, Wiley, 3rd ed. 2016; JMP version 2017, R version 2018, Python version 2019), Introductory Statistics and Analytics (Wiley, 2015), and Practical Statistics for Data Scientists, with Andrew Bruce and Peter Gedeck, (O'Reilly 2016). His books have been translated into Japanese, Chinese, Korean, German, Polish and Spanish.

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Mrs. Meena Badade

Mrs. Meena Badade

Mrs. Meena Badade has over 23 years teaching experience, leading courses in statistics at various levels of education and at different institutions nationally and internationally. She also has a number of research papers published in respected journals. In addition to academic practice, she has considerable corporate experience at Metric Consultancy, where she worked as a statistical consultant and data analyst for international clients, applying various statistical techniques to projects in several industries.

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Anuja Kulkarni

Ms. Anuja Kulkarni

Ms. Anuja Kulkarni has managed and taught over 125 online course sessions and more than 1000 students as an Assistant Teacher at The Institute for Statistics Education. She holds a Masters’ degree in Statistics from Kolhapur University, India, where she also taught undergraduate statistics. Ms. Kulkarni teaches Statistics, Optimization Methods and Predictive Analytics and assists in several other course topics here for over six years. In all, her passion is leading new students into the fascinating and practical world of statistics through the introductory statistics course series at The Institute.  

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Course Syllabus

Week 1

Study Design, Statistical Significance

  • Intro, Study Design
  • Measures of Central Location and Variability
  • Distance
  • Data Format
  • Variables
  • Graphs
  • Null Hypothesis
  • Resampling
  • Normal Distribution
  • Significance

Week 2

Categorical Data, Contingency Tables

  • Categorical Data
  • Graphical Exploration
  • Indexing
  • Simple Probability
  • Distributions
  • Normal Distribution again
  • 2-Way (Contingency) Tables
  • Conditional Probability

Week 3

More Probability, Random Sampling, The Bootstrap

  • Bayes Rule
  • Independence
  • Surveys
  • Random Sampling
  • Bootstrap

Week 4

Confidence Intervals

  • Point Estimates
  • Confidence Intervals
  • Formula Counterparts
  • Standard Error
  • Beyond Random Sampling

Class Dates

2022

Jun 3, 2022 to Jul 1, 2022

Jul 1, 2022 to Aug 5, 2022

Aug 5, 2022 to Sep 2, 2022

Sep 2, 2022 to Oct 7, 2022

Oct 7, 2022 to Nov 4, 2022

Nov 4, 2022 to Dec 2, 2022

Dec 2, 2022 to Jan 6, 2023

2023

Jan 6, 2023 to Feb 3, 2023

Feb 3, 2023 to Mar 3, 2023

Mar 3, 2023 to Apr 7, 2023

Apr 7, 2023 to Dec 3, 2023

2024

No classes scheduled at this time.

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Prerequisites

There are no prerequisites for this course.

The only mathematics you need is arithmetic.

This course requires the use of software. Please read the “Software” section below.

What Our Students Say​

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Jerrilyn Stringer

I thought this class was excellent, the material was very understandable, the examples and practice were great, and the teacher is phenomenal! Very happy with this course.

Jerrilyn Stringer
Jabil
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Michelle MacKinnon

Excellent format, with flexibility to work whenever time is available, and work a bit ahead as needed to work around other commitments

Michelle MacKinnon
Manager, Sales Analysis
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Frequently Asked Questions

Can I transfer or withdraw from a course?

We have a flexible transfer and withdrawal policy that recognizes circumstances may arise to prevent you from taking a course as planned. You may transfer or withdraw from a course under certain conditions.

  • Students are entitled to a full refund if a course they are registered for is canceled.
  • You can transfer your tuition to another course at any time prior to the course start date or the drop date, however a transfer is not permitted after the drop date.
  • Withdrawals on or after the first day of class are entitled to a percentage refund of tuition.

Please see this page for more information.

Who are the instructors at the Institute?

The Institute has more than 60 instructors who are recruited based on their expertise in various areas in statistics. Our faculty members are:

  • Authors of well-regarded texts in their area;
  • Advisory board members;
  • Senior faculty; and
  • Educators who have made important contributions to the field of statistics or online education in statistics.

The majority of our instructors have more than five years of teaching experience online at the Institute.

Please visit our faculty page for more information on each instructor at The Institute for Statistics Education.

Please see our knowledge center for more information.

What type of courses does the Institute offer?

The Institute offers approximately 80 courses each year. Topics include basic survey courses for novices, a full sequence of introductory statistics courses, bridge courses to more advanced topics. Our courses cover a range of topics including biostatistics, research statistics, data mining, business analytics, survey statistics, and environmental statistics.

Please see our course search or knowledge center for more information.

Do your courses have for-credit options?

Our courses have several for-credit options:

  • Continuing education units (CEU)
  • College credit through The American Council on Education (ACE CREDIT)
  • Course credits that are transferable to the INFORMS Certified Analytics Professional (CAP®)

Please see our knowledge center for more information.

Is the Institute for Statistics Education certified?

The Institute for Statistics Education is certified to operate by the State Council of Higher Education for Virginia (SCHEV). For more information visit: https://www.schev.edu/

Please see our knowledge center for more information.

Visit our knowledge base and learn more.

FAQs + Knowledge Base

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Additional Course Information

Organization of Course

This course takes place online at The Institute for 4 weeks. During each course week, you participate at times of your own choosing – there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.

At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and at the end of the week, you will receive individual feedback on your homework answers.

Time Requirements

This is a 4-week course requiring 10-15 hours per week of review and study, at times of your choosing.

Homework

Homework in this course consists of short answer problems, and includes exercises that require the use of computer software.

In addition to assigned readings, this course also has an exam, short narrated software demos, example software codes, and  supplemental readings available online.

Exam
Those seeking ACE credit, or who are certificate candidates needing to satisfy their introductory statistics requirement, must pass an online exam at the end of Statistics 2 – Inference and Association.

Course Text

All needed course material will also be provided electronically as part of the course.  The course is based on the book Introductory Statistics and Analytics: A Resampling Perspective by Peter Bruce, (2014, Wiley). It does not synchronize exactly with the course material, which has updates, but is a useful parallel reference if you want to have a printed book.

Software

In this course, software is needed for statistical analysis and simple resampling/simulation operations. We recommend one of these options:

  1. Regular Excel (not Excel Starter) and Resampling Stats for Excel (must have Windows)
  2. StatCrunch (Windows or Mac OS)
  3. R
  4. Python

Excel
You will need to have some facility with using formulas in Excel. If you don’t, please review either this tutorial or this tutorial before the course starts.

Resampling Stats for Excel
This is a commercial add-in for Excel, designed as a practitioner’s tool for doing resampling simulations. A free license is available to all course participants, while they are enrolled in the statistics.com sequence of introductory statistics courses. Runs only on Windows. Enrolled students will be given access to a free 1-year trial of Resampling Stats through the software download link on the main Stats course webpage.  You can also visit the Resampling Stats website and download the 1-year trial here.

StatCrunch
This is a very affordable web-based statistical software program, which also has simulation and resampling capabilities. Runs over the web, so can be used with both Windows and Mac. Resampling is not as intuitive as with Box Sampler and Resampling Stats for Excel.  Learn more at www.statcrunch.com.

Note for StatCrunch Users:  On all platforms, we recommend that you use the New version of StatCrunch.  All examples in the textbook supplement are based on the New version of StatCrunch.

R
R is a powerful opensource statistical scripting language that is widely recognized as an industry standard.  You will need to have familiarity with R and RStudio prior to taking the Statistics 1, 2 or 3 courses if you choose to use R as your software package.  Comprehensive supplemental materials are available for R users.  You can learn more about R here and RStudio here.

Python: Python is a language long used in computer science that has recently become quite popular in data science.  You will need to have familiarity with Python prior to taking the Statistics 1, 2 or 3 courses if you choose to use Python as your software package.  Comprehensive supplemental materials and support are available for Python users.  We recommend the use of Jupyter notebooks and the Anaconda installation package.

Software Uses and Descriptions | Available Free Versions
To learn more about the software used in this course, or how to obtain free versions of software used in our courses, please read our knowledge base article “What software is used in courses?” 

Course Fee & Information

Enrollment
Courses may fill up at any time and registrations are processed in the order in which they are received. Your registration will be confirmed for the first available course date unless you specify otherwise.

Transfers and Withdrawals
We have flexible policies to transfer to another course or withdraw if necessary.

Group Rates
Contact us to get information on group rates.

Discounts
Academic affiliation?  In most courses you are eligible for a discount at checkout.

New to Statistics.com?  Click here for a special introductory discount code.  

Invoice or Purchase Order
Add $50 service fee if you require a prior invoice, or if you need to submit a purchase order or voucher, pay by wire transfer or EFT, or refund and reprocess a prior payment.

Options for Credit and Recognition

This course is eligible for the following credit and recognition options:

No Credit
You may take this course without pursuing credit or a record of completion.

Mastery or Certificate Program Credit
If you are enrolled in mastery or certificate program that requires demonstration of proficiency in this subject, your course work may be assessed for a grade.

CEUs and Proof of Completion
If you require a “Record of Course Completion” along with professional development credit in the form of Continuing Education Units (CEU’s), upon successfully completing the course, CEU’s and a record of course completion will be issued by The Institute upon your request.

ACE CREDIT | College Credit
This course has been evaluated by the American Council on Education (ACE) and is recommended for college credit.  For recommendation details (level, and number of credits), please see this page. Please note that the decision to accept specific credit recommendations is up to the academic institution accepting the credit.

ACE Digital Badge
Courses evaluated by the American Council on Education (ACE) have a digital badge available for successful completion of the course.

Exam
Those seeking ACE credit, or who are certificate candidates needing to satisfy their introductory statistics requirement, must pass an online exam at the end of Statistics 2 – Inference and Association.

Supplemental Information

There is no supplemental content for this course.

Miscellaneous

There is no additional information for this course.

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Statistics 1 – Probability and Study Design
$489 | Enroll Now
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