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Lesson 1  Introduction to Statistical Research Methods 
Lesson 2  Visualizing Data 
Lesson 3  Central Tendency 
Lesson 4  Variability 
Lesson 5  Standardizing 
Lesson 6  Normal Distribution 
Lesson 7  Sampling Distributions 
Lesson 8  Estimation 
Lesson 9  Hypothesis Testing 
Lesson 10  tTests for Dependent Samples 
Lesson 11  tTests for Independent Samples 
Lesson 12  Intro to OneWay ANOVA 
Lesson 13  OneWay ANOVA: Test significance of differences 
Lesson 14  Correlation 
Lesson 15  Linear Regression 
Lesson 16  ChiSquared Tests 
Afterward  
Index 
Let’s say we apply some kind of intervention to a sample, and then find that the mean of this sample is (“I” for “intervention”). Could we use this to estimate the population parameters if everyone were to receive the same intervention?
We could guess that the new population mean, which we’ll call , would be somewhere around . From the limited information we have, the sample mean is our best estimate for the new population mean. We call this a point estimate since it’s a single value rather than a range of values.
Actually, a range of values is exactly what we want. In this lesson, we’ll calculate confidence intervals for where might be; in other words, we’ll be fairly confident that is between two particular values. We’ll determine what these values should be.
In Lesson 6 you learned that for a normal distribution, most values (about 95%) are within two standard deviations of the mean.
We can extend this concept to sampling distributions: approximately 95% of sample means will fall within the population mean.
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