a) What is the rho value (from Excel) and the associated p-value (from the online calculator)? Does the T-test suggest that the correlation is significant (P < 0.05)? What does this mean about the null hypothesis? Remember, the p-value is how likely it is that the null hypothesis is true, given our data. Always interpret your conclusions (based on the p-value) in "human terms." Don't just say "we reject/fail to reject the null hypothesis because the p-value is less than/greater than the alpha value of 0.05." While you should state this first (always report the p-value), the final interpretation is "penny age and oxidation are /are not correlated; older pennies are/are not more oxidized." B) Is there a chance that our statistical test found that there was a correlation between penny age and oxidation, when in reality there is not? Is this a Type I or Type II error? C) Does the histogram appear to show an overall difference in age (Year) between the more oxidized and the less oxidized groups of pennies? Note: a good way to interpret this graph is to look at the amount of overlap between the colored bars. If there is a lot of overlap, would you expect the two groups to be different in their ages? PROVIDED DATA rHO VALUE : -0.45 HISTOGRAM: asap
a) What is the rho value (from Excel) and the associated p-value (from the online calculator)? Does the T-test suggest that the
B) Is there a chance that our statistical test found that there was a correlation between penny age and oxidation, when in reality there is not? Is this a Type I or Type II error?
C) Does the histogram appear to show an overall difference in age (Year) between the more oxidized and the less oxidized groups of pennies? Note: a good way to interpret this graph is to look at the amount of overlap between the colored bars. If there is a lot of overlap, would you expect the two groups to be different in their ages?
PROVIDED DATA
rHO VALUE : -0.45
HISTOGRAM:
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