Population Parameters: Population Proportion, Standard Deviation, and Population Mean

In this unit, you will investigate the normal probability curve (the bell curve). Many variables, such as height and weight are "normally distributed." This means, for example, that if you were to collect 10,000 female adult human heights, the histogram of that data would be shaped like a "bell" (with "most" of the data near the center or mean).
Use the following z-table (also located in Course Resources) to assist you with answering the discussion topics.
18:34 After completing your readings for this unit, think about and share your response to the following questions:
Offer at least two examples of a population parameter that you cannot calculate, but that you can estimate. Some examples might be the true percentage of the number of bass in Lake Erie or the mean hours of sleep per night for all U.S. college students. In your own words, why do you think it is impossible to know the actual value of any population parameter?
A sample can be used to estimate a population parameter. how does the sample size affect the estimate?
To estimate a population parameter (such as the population mean or population proportion) using a confidence interval first requires one to calculate the margin of error, E. The value of the margin of error, E, can be calculated using the appropriate formula. The formula depends on whether one is estimating a mean or estimating a proportion.
a) The Margin of Error, E, for a 95% confidence interval for means is: E=1.96s/√n
where s is the sample standard deviation and n is the sample size.
b) Invent a quantitative variable, such as age, weight, exam score, etc. Thinking about that variable, create a small set of data (30 data values) to describe that variable. Use Excel to calculate the sample mean of your data and the sample standard deviation. If you create 30 values, the sample size is 30. Then, calculate the margin of error.