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Learn the essential techniques of statistics for data analysis using the world’s most used and famous spreadsheet program Microsoft Excel.

The [course_title] course teaches you histograms, Pareto charts, Boxplots, Bayes’ theorem, and others. You will explore the core principles of statistics and basic probability—from both the conceptual and applied perspectives. The course also focuses on statistics, basic probability, random variables, sampling and confidence intervals, and hypothesis testing. Finally, you will learn to explore these concepts and principles using the environment, functions, and visualizations of Excel.

### Assessment

This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.

### Certification

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Course Credit: Microsoft.

### Course Curriculum

 Introduction Online Courses from Microsoft 00:02:00 Welcome from Wayne Winston 00:01:00 Welcome from Liberty Munson 00:01:00 Welcome from Wayne and Liberty 00:02:00 Lesson 1 Individuals and Variables 00:01:00 Numerical and Categorical Data 00:01:00 Types of Data 00:05:00 What is a Histogram? 00:02:00 Histograms and Creating a Histogram in Excel 00:03:00 Types of Histograms and Skewness 00:03:00 Computing Mean, Median, Variance, and Standard Deviation 00:05:00 Range, Variance, and Standard Deviation 00:02:00 Computing Mean, Median, Variance, and Standard Deviation 00:05:00 Skewness 00:03:00 Working with Descriptive Statistics using Analysis ToolPak 00:02:00 Working with Descriptive Statistics using Analysis ToolPak 00:07:00 Rule of Thumb and Identifying Outliers 00:02:00 Rule of Thumb and Identifying Outliers Example 00:05:00 Computing Average, Median, Variance, Standard Deviation, and Skewness 00:08:00 RANK, LARGE, and SMALL Functions 00:05:00 Geometric Mean and Compound Annual Growth Rate (CAGR) 00:02:00 Geometric Mean and CAGR 00:05:00 Boxplots 00:02:00 What is a Boxplot? 00:04:00 Creating a Boxplot 00:02:00 Boxplots for Comparing Multiple Populations 00:03:00 Boxplots for Comparing Multiple Populations on Multiple Variables 00:02:00 Nominal Data and Ordinal Data 00:03:00 Summarizing Nominal Data with a Column Chart or Pie Chart 00:04:00 Summarizing Ordinal Data with a Column Chart 00:01:00 Hierarchical Data 00:03:00 What is Hierarchical Data? 00:02:00 80-20 Rule and Pareto Principle 00:02:00 80-20 Rule and Pareto Principle 2 00:01:00 Creating a Pareto Chart for Complaints Example 00:02:00 Lesson 2 Introduction to Probability 00:02:00 Axioms of Probability 00:01:00 Introduction to Probability 00:01:00 Law of Complements 00:01:00 Law of Complements in Excel 00:04:00 Mutually Exclusive Events and Finding Prob (A or B) 00:01:00 Mutually Exclusive Events in Excel 00:05:00 Joint Probabilities 00:02:00 Independent Events 00:01:00 Definition of Independent Events 00:08:00 Further Examples of Independent Events 00:05:00 Conditional Probability 00:05:00 Definition of Conditional Probability 00:06:00 Relationship to Independent Event 00:01:00 Finding Joint Probabilities 00:02:00 Further Examples of Conditional Probability 00:04:00 Unions 00:01:00 Law of Total Probability 00:03:00 Law of Total Probability in Excel 00:06:00 Further Discussion on the Law of Total Probability 00:02:00 States of the World, Prior Probabilities, and Likelihoods 00:03:00 Bayes Theorem 00:01:00 Bayes Theorem Example 00:03:00 Bayes Theorem in Excel 00:07:00 Law of Total Probability 00:03:00 States of the World, Prior Probabilities, and Likelihoods 00:04:00 Bayes Theorem 00:01:00 Bayes Theorem Example 00:03:00 Another Example of Bayes Theorem 00:02:00 Bayes Theorem in Excel 00:07:00 Basic Probability Review 00:09:00 Lesson 3 What is a Random Variable? 00:01:00 Random Variables in Excel 00:02:00 Discrete Random Variables 00:01:00 Discrete Random Variables and Probability Mass Function (PMF) 00:02:00 Continuous Random Variables 00:04:00 Independent Random Variables 00:01:00 Independent Random Variables in Excel 00:03:00 Independent Random Variables in Excel 00:02:00 Finding the Mean of a Discrete Random Variable 00:01:00 Finding the Mean of a Discrete Random Variable in Excel 00:03:00 Finding the Mean of a Discrete Random Variable in Excel 00:03:00 Finding the Variance and Standard Deviation of a Discrete Random Variable 00:01:00 Finding the Variance and Standard Deviation of a Discrete Random Variable in Excel 00:04:00 Illustrating Mean, Variance, and Standard Deviation through Simulation 00:01:00 Mean of Sum of Random Variable 00:01:00 Mean of Sum of Random Variables in Excel 00:02:00 Variance and Standard Deviation of Sum of Independent Random Variables 00:04:00 Mean, Variance, and Standard Deviation of Binomial Random Variable in Excel 00:02:00 Binomial Random Variable 00:01:00 Binomial Random Variable and the BINOM.DIST.RANGE Function 00:03:00 Binomial Probabilities 00:02:00 Examples of Computing Binomial Probabilities 00:04:00 Mean, Variance, and Standard Deviation of Binomial Random Variable 00:01:00 Mean, Variance, and Standard Deviation of Binomial Random Variable in Excel 00:02:00 Poisson Random Variable 00:02:00 Poisson Random Variable Usage 00:02:00 Poisson Random Variable and the POISSON.DIST Function 00:02:00 Poisson Probabilities 00:01:00 Mean, Variance, and Standard Deviation of Poisson Random Variable 00:01:00 Definition of Normal Random Variable 00:01:00 Normal Random Variable in Excel 00:03:00 NORM.DIST and NORM.INV Functions 00:03:00 Examples of Normal Probabilities 00:02:00 Examples of Normal Percentiles 00:02:00 Definition of Central Limit Theorem 00:02:00 Central Limit Theorem in Excel 00:01:00 Computing Probabilities with Central Limit Theorem 00:04:00 Further Central Limit Theorem Example 00:04:00 Definition of Z Scores 00:03:00 Z Scores Definition and the STANDARDIZE Function 00:03:00 Computation of Z Scores 00:06:00 Highlighting Outliers via Z Scores 00:02:00 Lesson 4 Definition of Population and Population Parameters 00:01:00 Definition of Population and Population Parameters 00:02:00 Populations and Samples 00:01:00 Definition of Population and Population Parameters 00:03:00 Samples and Sample Statistics 00:01:00 Sampling Strategies 00:02:00 Simple Random Sample 00:02:00 Problems in Sampling 00:03:00 Mean, Variance and Standard Deviation of Sample Mean (Xbar) 00:03:00 Xbar and Mean, Variance, and Standard Deviation of Xbar 00:03:00 Examples of Sample 00:02:00 Estimate Population Proportion using P-hat 00:02:00 Estimate Population Proportion using P-hat in Excel 00:02:00 Standard Normal 00:01:00 Standard Normal and the .S Functions 00:02:00 Confidence Interval for Population Mean 00:02:00 Confidence Interval Examples 00:02:00 95% Confidence Interval for Population Mean 00:04:00 Demonstration of Meaning for Confidence Interval 00:01:00 95% Confidence Interval for Population Proportion 00:02:00 Blyth’s Formula for Proportion Confidence Interval 00:03:00 Sample Size for Estimating Population Mean 00:01:00 Sample Size for Estimating Population Mean 1589 00:02:00 Sample Size for Estimating a Population Proportion 00:03:00 Finite Correction Formula 00:02:00 Finite Correction Factor 00:04:00 Finite Correction Formula for Estimating Population 00:02:00 Sample Size and the Finite Correction Factor 00:02:00 Lesson 5 Null and Alternative Hypotheses 00:02:00 Hypothesis Testing and Null and Alternative Hypotheses 00:02:00 Upper One-Sided Alternative 00:02:00 Upper One-Sided Alternative 2 00:02:00 Lower One-Sided Alternative 00:04:00 Two-Tailed Alternative 00:02:00 Choosing between One-Tailed or Two-Tailed Test 00:01:00 One-Tailed or Two-Tailed Test 00:02:00 Type I and Type II Error 00:03:00 Type I and Type II 00:02:00 More on the Null and Alternative Hypothesis 00:02:00 Critical Region 00:02:00 Critical Region in Excel 00:03:00 One Sample Z-Test 00:02:00 Critical Region 00:02:00 One Sample Z Test Example 00:02:00 P-Values 00:02:00 P-Values and Application to One Sample Z-Test 00:05:00 Critical Region, P-Values, and T.INVERSE Function 00:02:00 One Sample T-Test : One Tailed 00:02:00 One Sample T-Test : Two Tailed 00:02:00 One Sample T-Test in Excel 00:02:00 Single Sample Test for Population Proportion 00:02:00 Single Sample Test for Population Proport 00:02:00 Single Sample Test for Population Proportion Example 00:06:00 Single Sample Test for Population Proportion 00:02:00 Single Sample Test for Population Proportion in Excel 00:02:00 Single Sample Test for Population Proportion Example 00:02:00 Testing Equality of Variances 00:02:00 Definition of Testing Equality of Variances and the F.TEST Function 00:02:00 Testing Equality of Variances Example 00:02:00 Testing Equality of Variances 00:02:00 Definition of Testing Equality of Variances and the F.TEST Function 00:01:00 Testing Equality of Variances Example 00:03:00 Four Types of Tests 00:02:00 Which of the Four Types of Tests Should You Use and When 00:02:00 Two Sample Z-Test 00:02:00 Two Sample Z-Test in Excel 00:02:00 Equal Variance T-Test 00:02:00 Equal Variance T-Test in Excel 00:02:00 Unequal Variance T-Test 00:02:00 Unequal Variance T-Test in Excel 00:02:00 Idea of Pairing Samples 00:00:00 Idea of Pairing Samples 00:01:00 Two Sample Z-Test in Excel 00:03:00 Two Sample Z-Test 00:02:00 Equal Variance T-Test 00:02:00 Unequal Variance T-Test 00:03:00 Unequal Variance T-Test in Excel 00:03:00 Idea of Pairing Samples 00:03:00 T-Test Paired Two Sample 00:02:00 Example of T-Test Paired Two Sample 00:03:00 Contingency Table and Hypothesis of Independence 00:02:00 Example of Contingency Table and Hypothesis of Independence 00:02:00 Computation of Chi Squared Statistic 00:03:00 Computation of Chi Squared Statist 00:02:00 Conducting the Hypothesis Test and Computing the P-Value 00:04:00 Assment Submit Your Assignment 00:00:00 Certification 00:00:00

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