The percent increase is 125 %
<em><u>Solution:</u></em>
Given that the past the price of popcorn at a movie theatre increased from $2.00 to $4.50
<em><u>To find: percent increase</u></em>
The percent increase between two values is the difference between a final value and an initial value, expressed as a percentage of the initial value.
<em><u>The percent increase is given as:
</u></em>
Here initial value = 2 and final value = 4.50
<em><u>Substituting the values in above formula, we get</u></em>
Thus percent increase is 125 %
Answer:
x-5
Step-by-step explanation:
0.5 cups × 8 oz/cup = 4 oz
Answer:
x < 3
Step-by-step explanation:
-12 < -7x -5 +14
add -5 and 14: -12 < -7x + 9
minus 9 from both sides: -7x > -21
divide both sides by -7: x < 3
the sign flips when you divide
Answer:
C) The Spearman correlation results should be reported because at least one of the variables does not meet the distribution assumption required to use Pearson correlation.
Explanation:
The following multiple choice responses are provided to complete the question:
A) The Pearson correlation results should be reported because it shows a stronger correlation with a smaller p-value (more significant).
B) The Pearson correlation results should be reported because the two variables are normally distributed.
C) The Spearman correlation results should be reported because at least one of the variables does not meet the distribution assumption required to use Pearson correlation.
D) The Spearman correlation results should be reported because the p-value is closer to 0.0556.
Further Explanation:
A count variable is discrete because it consists of non-negative integers. The number of polyps variable is therefore a count variable and will most likely not be normally distributed. Normality of variables is one of the assumptions required to use Pearson correlation, however, Spearman's correlation does not rest upon an assumption of normality. Therefore, the Spearman correlation would be more appropriate to report because at least one of the variables does not meet the distribution assumption required to use Pearson correlation.