DB, I am more of a results-type guy, and it seemed to me that probably most of the replies where a little to theoretical for you to apply to your little stat question. Here's my reply for you, I welcome discussion from others.
First, you need to phrase your question in appropriate stat lingo. Here is what I am assuming you are wanting to know. Are the test scores for my two classes statistically different? Here's what you do in Excel: 1) Make one column for Class A. List all the test scores for all the exams that they have taken (sounds like two tests, but if it is more, list all of them). 2) Make another column for Class B and list all there scores. The two columns will be of different lengths, but that is OK. 3) Is your Data Analysis Toolpak loaded in your Excel? Go to "Tools". Do you have "Data Analysis"? If not, get your Excel disks and go to "Tools" and click "Add-ins". It will then instruct you to load your Excel disk. 4) Go to "Tools" "Data Analysis" and then choose "t-Test: Two Sample Assuming Equal Variances". This performs a statistical test to compare two sample means to see if there is adequate information to show that they are significantly different. Since you are looking at sample data, we can assume that the means of any two classes will not be exactly the same. The question is then whether or not the difference is statistically significant. Realize that the less data that you have, the harder it is to demonstrate that the means are different. Yes, we are making the assumption that the variances are equal, I consider that a reasonable assumption for two classes of sixth graders taking the same tests. 5) Enter in the Class 1 column for "Variable 1 Range:". Go ahead and include the column header with the data. That way the results will uses the headers and makes it easier to interpret. Enter the Class 2 column for "Variable 2 Range:". For "Hypothesized Mean Difference:" enter 0. Our "null hypothesis" is that the two classes are not significantly different in test-taking abilities. That is, the two population means are equal. Click "Labels" and leave the alpha at .05. This is similar to a 95% confidence interval. Why the majority of stats are done with 95% confidence is somewhat arbitrary, but it is what is used most of the time. I can think of no reason that you would need to consider a different alpha. Then click "OK". 6) When you look at the results, you have to determine if you meant to perform a 1-tailed test or a 2-tailed test. In both cases, the null hypothesis is that the two means are equal. If your alternative hypothesis is that the two means are not equal, you want to use a 2-tailed test. If your alternative hypothesis is that the mean of Class 2 is greater than the mean of Class 1, then you would want to use a 1-tailed test. Which one is correct? Well let's consider the problem as if it was summer and none of the tests had been taken yet. You plan to examine the test results of your two classes to see if there average test scores are significantly different or not. At this point in time, you don't know which class is going to be better, therefore your alternative hypothesis can only be that the two means are not equal. Thus we are performing a 2-tailed test. The null hypothesis is considered rejected at the 5% level if the "t Stat" is greater than the "t Critical two-tail". So if the t stat is greater than the t critical, you conclude that the mean test scores for the two classes are significantly different. Hope that helps. Let me know if you can't get your hands on the Analysis Toolpak and I'll write out the proper equations. John Weaver <[EMAIL PROTECTED]> wrote in message news:[EMAIL PROTECTED] [EMAIL PROTECTED] ([EMAIL PROTECTED]) wrote in message news:<[EMAIL PROTECTED]>... > I ran a z test on two sets of scores using the Excel data analysis > tool to seek to determine whether the difference in the means were > statistically significant. What I do not understand is how to read > the results of the z test Excel returns. It give me a "z", "P" one > tail and "P" two tail. Can anyone explain to me how to interpret > these results? Thanks. I really do appreciate the time you folk took to respond, but I am still in the dark. So let me be a bit more explicit and see if what I need makes more sense. I am a sixth grade teacher. I have two sets of reading scores (standard scores with a range of 27 to 55). One set has 40 students and the other has 65. I enter each score in a column in Excel for each class. I get the mean, st. dev. and variance from Descriptive Statistics. On one test the difference in mean scores is less than 2 points. On another test the difference is 12 points. Common sense tells me there is a significant difference in the two sets of scores on the test with 12 points difference. My question is: is the difference of 2 points statistically significant or the result of chance? If my assumption is correct and one class did significantly better than the other on one test and on the other the difference in performance is (probably) not statistically significantly different then is that a correct assumption? So somewhere between 12 points and 2 points I can guess there is a significant difference but less than that it is not. I asked a math teacher how to determine that point on any given set of scores and was told to run a z test. I was told a t test is used to test whether a sample's mean is representative of the total population's mean. So I used a z test. In Excel what is returned is a "z" score, a P score for one tail and a P score for two tail for a hypothesized mean of .05. Can someone tell me how to interpret the numbers returned for z, P one tail and P two tail, assuming the z test is the correct procedure. If not, what do I use and how do I interpret the results Excel returns? . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
