When reading the National vs. Local Unemployment Rate in chapter 8, If it wasn’t for the following statement

• Hello,

When reading the National vs. Local Unemployment Rate in chapter 8, If it wasn’t for the following statement, “So, what does this say about the local unemployment picture in your area versus the national unemployment situation? Since a major portion of the interval for the local unemployment rate is below 5.1%, is it reasonable to conclude that the local unemployment rate is below the national unemployment rate? Not really.” (Mann S. P. 337) I would have just read through it and thought that I understood the concept. But this statement made me question the values used and the calculation so I was forced to go back and read what it’s actually doing. Because the local unemployment rate would have the range between 4.2% and 5.2%, and the national unemployment rate was 5.1, you can’t truly be 100% sure that the local unemployment rate is actually lower than the national.

 

Good point, the local unemployment rate is within the interval estimate of the national rate for unemployment.  Can anyone tell us what assumptions I am making in this statement?

 

 

In week 4, we were asked to explain the calculation for “the 95% confidence interval” related to the milk data assignment. I had to do a bit of a research to understand what all of it means as it was not mentioned any where in the chapters 6 and 7 materials.

Now, I understand the true formula for calculating the confidence levels:

But, before starting this calculation we should first find the area of each tail, that is

Then divide results by 2, so you can use the Table VI in Appendix B to get the confidence level for the particular percentage.

 

Good discussion of the calculation of a confidence interval.  However, you can only use the z-score when you have a sample size of 30 or more.  Can anyone tell us what we need to use if the sample size is less than 30?

 

• After defining what estimation is, there are two types of estimation and they are point estimation and interval estimation. the point estimation means that we used values from a sample statistics to estimate the population parameter. also, the values of the corresponding sample statistics equal to the point estimate of a population parameter. as for the interval estimation, it contains the corresponding population parameter with a certain confidence level. the inverted estimation is concentrated around the point estimation. it is usually defined by two numbers whereas the point estimation is defined by a single statistic value. I believe these two estimations are applied for different situations.

 

Do you agree or disagree?? Why or why not?

 

 

• Hello,

 

For each interval surrounding the point estimate, based on adding or subtracting marginal errors (denoted by E) to the point estimate, a particular Confidence level is granted. This is called the confidence interval. In simple terms, when sample testing things, data or surveys, we are not looking at the whole picture. Depending on what it is that we are looking at, we may have different percentage of confidence about how accurate the results come up to. This is the same thing as the confidence level. And the different variables that can shift the percentage of confidence to higher or lower is the confidence intervals.

 

Do you agree or disagree?? Why or why not??