2. A sweater costs $35. Find the total cost of the sweater if the sales tax is 5%.
2 answers:
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Answer:
0.4010 = 40.10% probability that the sample mean would differ from the population mean by more than 0.8 millimeters
Step-by-step explanation:
To solve this question, we need to understan the normal probability distribution and the central limit theorem.
Normal probability distribution:
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.
Central limit theorem:
The Central Limit Theorem estabilishes that, for a random variable X, with mean and standard deviation
, the sample means with size n of at least 30 can be approximated to a normal distribution with mean
and standard deviation
In this problem, we have that:
Either the sample mean differs by 0.8 mm or less from the population mean, or it differs by more. The sum of these probabilities is decimal 1.
Probability it differs by less than 0.8mm
pvalue of Z when X = 139 + 0.8 = 139.8mm subtracted by the pvalue of Z when X = 139 - 0.8 = 138.2 mm
X = 139.8
By the Central Limit Theorem
has a pvalue of 0.7995
X = 138.2
has a pvalue of 0.2005
0.7995 - 0.2005 = 0.5990
What is the probability that the sample mean would differ from the population mean by more than 0.8 millimeters?
p + 0.5990 = 0.4010
0.4010 = 40.10% probability that the sample mean would differ from the population mean by more than 0.8 millimeters
Answer:
For this case the value of r = -0.66
Now we can calculate the determination coeffcient:
And then we can conclude that 43.56% of the variation in y can be explained by the explanatory variable
And then 100-43.56 = 56.44 % of the variation in y that cannot be explained by the explanatory variable
Step-by-step explanation:
For this case we need to calculate the slope with the following formula:
Where:
And we can find the intercept using this:
And the model obtained for this case is:
The correlation coefficient is a "statistical measure that calculates the strength of the relationship between the relative movements of two variables". It's denoted by r and its always between -1 and 1.
And in order to calculate the correlation coefficient we can use this formula:
For this case the value of r = -0.66
Now we can calculate the determination coeffcient:
And then we can conclude that 43.56% of the variation in y can be explained by the explanatory variable
And then 100-43.56 = 56.44 % of the variation in y that cannot be explained by the explanatory variable