I am confused I worked out the following and I got the wrong answer
Can anyone explain where I went wrong for future reference please it is in case it ever comes up again
Equation of Yi=a + bxi.
-0.5(4.86/3.50) or 4.86/3.50*-0.5
Time spent on PC predictor
Time spent working on PC response
Standard Deviation 4.86 pc time
Standard Deviation time spent
working is 3.50
Correlation -0.5
It seems like you are trying to calculate the equation of Yi using the equation Yi = a + bxi. However, you encountered an issue and got the wrong answer. Let's go through the steps and try to figure out where you went wrong.
First, you mentioned the standard deviation for PC time as 4.86 and the standard deviation for working time as 3.50. These values indicate the variability in the data, but they are not directly related to calculating the Yi values or the equation itself.
Next, you mentioned a correlation of -0.5. Correlation measures the strength and direction of a linear relationship between two variables. In this case, you have the correlation between PC time and working time. A correlation of -0.5 suggests a negative linear relationship, meaning that as PC time increases, working time tends to decrease.
Now, to calculate the equation of Yi, we need more information. Specifically, we need the values for the intercept (a) and the slope (b) in the equation Yi = a + bxi. It seems you didn't provide these values, and without them, we cannot proceed with finding the equation of Yi.
To find the intercept (a) and the slope (b), you would typically need a set of data points for both xi (PC time) and Yi (working time). With this data, you can use statistical methods like linear regression to estimate the values of a and b.
Once you have the values of a and b, you can substitute them into the equation Yi = a + bxi to calculate the expected values of Yi. If you have specific data points for PC time, you can then substitute them into the equation to get the corresponding working time values (Yi).
Without the specific values of a and b or the data points, it is challenging to pinpoint exactly where you went wrong in your calculations. I recommend providing more information or specific data points so we can help you further.