Author
Released
6/11/2019- Explain how to calculate simple probability.
- Review the Excel statistical formulas for finding mean, median, and mode.
- Differentiate statistical nomenclature when calculating variance.
- Identify components when graphing frequency polygons.
- Explain how t-distributions operate.
- Describe the process of determining a chi-square.
Skill Level Beginner
Duration
Views
- Data is seemingly everywhere these days. Why? 'Cause it's easy to collect. Not only that, it's getting cheaper to store. But data sitting in storage is just that. It's numbers and variables and figures. Data is pointless if we can't understand it and put it to good use. That's where statistics can help. You can think of statistics in two different ways. Descriptive, which deals with organizing and presenting data, and inferential, which makes predictions based on sample trends. Fortunately, Microsoft Excel can help us take plain old data and analyze it. And that's what we're going to do in this course. Mind you, this is not a course on Excel. We're just using a software to get to the heart of our data. But what I will teach is stats around samples and populations. We'll also take a look at how to organize and describe data while using Excel's functions, graphics, and statistical capabilities. Once we're done describing the data, we'll look at how to analyze data and make decisions on what we find. Hello, I'm Joseph Schmuller. I'll be your host for this course. I've taught statistics courses in both the undergraduate and graduate levels for many years, and I'm the author of the four editions of Statistical Analysis with Excel for Dummies. I hope you enjoy taking this course as much as I enjoyed creating it. Let's get started.
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Introduction
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What is data?1m 37s
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The big picture2m 11s
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1. Excel Statistics Fundamentals
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Using Excel functions6m 12s
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Working with Excel graphics4m 23s
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2. Types of Data
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Differentiating data types4m 20s
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3. Probability
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Defining probability1m 55s
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Calculating probability6m 14s
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4. Central Tendency
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The mean and its properties2m 16s
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Working with the median2m 23s
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Working with the mode1m 53s
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5. Variability
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Understanding variance4m 30s
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Z-scores3m 2s
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6. Distributions
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Probability distributions4m 10s
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7. Normal Distributions
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8. Sampling Distributions
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Meeting the t-distribution2m 24s
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9. Estimation
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Confidence in estimation4m 45s
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10. Hypothesis Testing
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11. Testing Hypotheses about a Mean
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12. Testing Hypotheses about a Variance
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The chi-squared distribution3m 37s
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13. Independent Samples Hypothesis Testing
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14. Matched Samples Hypothesis Testing
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15. Testing Hypotheses about Two Variances
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16. The Analysis of Variance
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Introducing ANOVA6m 22s
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Applying ANOVA1m 41s
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17. After the Analysis of Variance
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18. Repeated Measures Analysis
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What is repeated measures?5m 48s
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19. Hypothesis Testing with Two Factors
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Statistical interactions5m 4s
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Two-factor ANOVA5m 21s
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20. Regression
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Multiple regression analysis3m 16s
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21. Correlation
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Understanding correlation2m 39s
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Conclusion
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Next steps1m
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Video: What is data?