1. There is a correlation between scores of an assessment and prep hours
I'm assuming there's no other figure or anything; that this is the entire problem.
I'll further assume by correlation they mean positive correlation - more hours studying means a better score.
<u>Slope of 2.35 is reasonable.</u> CHECK
Correlation doesn't tell us what the slope is; any positive slope is reasonable. It will depend on the scoring levels of the test.
<u>Correlation should be fairly strong to strong</u>
If all we know is correlation we don't know if it's strong. No check.
<u>Based on the study, ... sleep ...</u>
We don't know anything about sleep; no check
<u>Causation ...</u>
It's an old saw: Correlation does not imply causation. No check
<u>A value of r = -.88 is reasonable</u>
Here when we say there's a correlation we seem to mean a positive correlation, so I'm going with not reasonable, no check.
2. Correlation between # training days and amount of rainfall. Increasing rainfall during spring training, less after.
Here we have what's likely a negative correlation -- more rain means less training.
<u>r = 0.79 is possible</u>
I'll go with no check here because we expected a negative correlation.
<u>... causation ....</u>
No check.
<u>high amount of rainfall</u>
Correlations tells us how the variations from average of two things line up. The value of the average itself doesn't matter. No check
<u>Strength of correlation is hard to determine with information given</u>
That's a CHECK. We have no information on the strength.
<u>Slope = -9.84 is reasonable</u>
<u>CHECK</u>
It's negative; the exact value will depend on units of things.
