Understanding Coen's D and Effect Size

The video tutorial explains hypothesis testing and the importance of calculating effect size to understand the strength of an effect. It discusses two samples, A and B, with different medications and their sample means compared to a population mean. The tutorial introduces Coen D as a method to calculate effect size, emphasizing its role in determining the magnitude of differences found in statistical analyses.

What is the primary purpose of hypothesis testing?

• To determine the exact value of a population mean

• To calculate the effect size of a sample

• To find the standard deviation of a sample

• To assess whether a sample is significantly different from a population

In the context of the video, what is the population mean?

• 100

• 200

• 120

• 150

What is the sample mean of Sample A?

• 120

• 100

• 200

• 150

What is the sample mean of Sample B?

• 150

• 100

• 120

• 200

What does hypothesis testing fail to provide?

• The population mean

• The strength or magnitude of the effect

• The standard deviation

• The exact sample size

What is effect size a measure of?

• The standard deviation

• The sample size

• The strength of an effect

• The difference between two population means

What is the role of special statistics in hypothesis testing?

• To determine the population mean

• To calculate the sample size

• To measure the strength of the actual difference

• To find the standard deviation

What is Coen's D used for?

• Determining the population mean

• Measuring the effect size

• Finding the standard deviation

• Calculating the sample mean

How is Coen's D calculated?

• Mean difference divided by the standard deviation

• Sample size divided by the population mean

• Standard deviation multiplied by the mean

• Population mean divided by the sample mean

What does a Coen's D value of 0.2 indicate?

• A large effect

• A medium effect

• No effect

• A small effect