00:01
The following is a solution for number 10, and we're looking at the overall, or this researcher at least, looked at the overall contentment to 30 married couples and a higher grade meaning that they have a greater contentment.
00:12
So we're testing that there is no difference between husbands and wives and their perception of contentment.
00:19
And the alternative saying that there is a difference, and we're looking at this at the 1 % level of significance.
00:25
So we need a test statistic and we also need a p value.
00:28
And what we're going to do is we're going to explicitly compare that p value with our alpha value, and that's going to tell us whether to reject or not reject.
00:35
Now, there are 30 data values here, really 60, but l1 is the husband.
00:42
So, you know, this one has a, i don't know what the scale is out of, hopefully not 100, because most are in the 40s and 50s, but 47 is the score for the male, or the husband, and then l2 is his wife.
00:56
Okay, so these are the married couples.
00:59
Scores so you can kind of see i scroll down but there are 30 in total okay and now i just need l3 to find those differences so if i click on l3 while 3 is highlighted i go to second one minus second two and that codes this column to find the differences there so l3 is really my data set so now if i go to stat and test this is now just a one sample t test using those differences as my one sample.
01:33
So i go to t test and the data is the input, mu1, i'm sorry, mu zero is just zero, so that meaning that there is no difference.
01:42
The list is l3 frequency is one, and then it's not equal to.
01:46
So the null hypothesis or the alternative hypothesis is not equal to, meaning that there is a difference between males and females or husbands and wives and their contentment.
01:54
So we calculate, and my test statistic is 3 .3...