Tristan records the number of customers who visit the store each hour on a Saturday. His data representing the first seven hours
2 answers:
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Answer:
Based on the analysis, the 95% confidence interval is specified as (0.2789;3.055)
The question regarding the 95% confidence interval's ability to ascertain potential differences in measurements between the two indenters is as follows:
Indeed, the confidence interval does not include the value 0, thus indicating that the Diamond values significantly exceed those of the Steel Ball at a 5% significance level.
Step-by-step explanation:
Here is the dataset in consideration:
specimen 1 2 3 4 5 6 7 8 9
Steel Ball 51 57 61 70 68 54 65 51 53
Diamond 53 55 63 74 69 56 68 51 56
By calculating the differences between diamond and steel ball measurements, we create the dataset:
d: 2, -2, 2, 4, 1, 2, 3, 0, 3
In the next step, we compute the mean difference
Following that, we determine the standard deviation of the differences, arriving at:
A confidence interval refers to "a range of values that’s likely to encompass a population value with a certain level of confidence. It is typically expressed as a percentage indicating where a population mean falls within an upper and lower limit."
The margin of error represents the extent to which values diverge above and below the sample statistic in a confidence interval.
Normal distribution, is described as a "probability distribution that is symmetric about the mean, illustrating that data points close to the mean occur more frequently than those further away."
The confidence interval for the mean is derived using the following formula:
(1)
To calculate the critical value , we first determine the degrees of freedom using:
Given a confidence level of 0.95 or 95%, the appropriate critical value can be found using Excel, a calculator, or a table. The Excel command would be: "=-T.INV(0.025,9)". Therefore, we observe that .
Finally, we can substitute all our findings into formula (1):
In this case, the 95% confidence interval is calculated as (0.2789;3.055)
In determining if the two indenters yield distinct measurements, we find that the confidence interval does not enclose zero, allowing us to conclude that Diamond readings greatly surpass Steel Ball readings at the 5% significance level.
Answer:
1. 3.767
2. 0.145
Step-by-step explanation:
Define X as the exam scores and Y as the number of drinks.
X Y X-Xbar Y-Ybar (X-Xbar)(Y-Ybar) (X-Xbar)² (Y-Ybar)²
75 5 -2.3 2.3 -5.29 5.29 5.29
92 3 14.7 0.3 4.41 216.09 0.09
84 2 6.7 -0.7 -4.69 44.89 0.49
64 4 -13.3 1.3 -17.29 176.89 1.69
64 2 -13.3 -0.7 9.31 176.89 0.49
86 7 8.7 4.3 37.41 75.69 18.49
81 3 3.7 0.3 1.11 13.69 0.09
61 0 -16.3 -2.7 44.01 265.69 7.29
73 1 -4.3 -1.7 7.31 18.49 2.89
93 0 15.7 -2.7 -42.39 246.49 7.29
sumx=773, sumy=27, sum(x-xbar)(y-ybar)= 33.9, sum(X-Xbar)²= 1240.1,sum(Y-Ybar)²= 44.1
Xbar=sumx/n=773/10=77.3
Ybar=sumy/n=27/10=2.7
1.
Cov(x,y)=33.9/9
Cov(x,y)=3.76667
Thus, the sample covariance of exam scores and energy drink consumption is 3.767
2.
Cor(x,y)=r=33.9/233.85553
Cor(x,y)=r=0.14496
The sample correlation coefficient for the relationship between exam scores and energy drink consumption is 0.145.