I believe it's C because 15 with an exponent of 5 is 15 x 15 x 15 x 15 x 15.
So that's basically larger than 15 x 15 x 15 x 15.
Common sense.
Answer:
77.4% probability that a data value is between 36 and 41
Step-by-step explanation:
Problems of normally distributed samples are solved using the z-score formula.
In a set with mean 
and standard deviation 
, the zscore of a measure X is given by:
The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.
In this question, we have that:
What is the probability that a data value is between 36 and 41?
This is the pvalue of Z when X = 41 subtracted by the pvalue of Z when X = 36.
X = 41
has a pvalue of 0.933
X = 36
has a pvalue of 0.159
0.933 - 0.159 = 0.774
77.4% probability that a data value is between 36 and 41
Answer: -14
Step-by-step explanation: Here we're asked to simplify -|-14| so we
start by simplifying the absolute value of -14.
Remember that the absolute value of
any positive or negative integer is positive.
So the absolute value of -14 is 14.
So we write (14) in parenthses like I have just done.
Next, we bring down the negative sign
that was outside the absolute value.
So we're left with -(14) or -14.
Answer:
A
Step-by-step explanation:
= 180-116= 64°
there fore ur answer is A
Answer:
5.47% of the total variation between the two variables can be explained by the regression line.
Step-by-step explanation:
Given :
R value = 0.234
The R value is the correlation Coefficient ; which gives the type and level of correlation between two variables.
However, to Obtian the percentage variation which can be explained by by the regression line, we have to obtain the Coefficient of determination, R².
R² value is Obtained by taking the squared of the correlation Coefficient
Hence,
R² = 0.234² = 0.054756
R² = 0.05476 * 100% = 5.4756%
Hence, R² = 5.48%
This is interpreted as ; 5.47% of the total variation between the two variables can be explained by the regression line.
