1 answer:
Answer:
i)
Find the attached
ii)
The mathematical model that best fits the data is;
The quadratic model
Step-by-step explanation:
i)
A scatter-plot can easily be constructed using applications such as Ms. Excel.
In Ms. Excel, enter the data into any two adjacent columns. Next, highlight the data, then click the insert ribbon and select the scatter-plot option.
Excel returns a scatter-plot chart as shown in the attachment below.
ii)
After obtaining the scatter-plot, we shall need to add a trend line in order to determine the mathematical model that best fits the data given.
Click anywhere inside the chart, then select the design tab under chart tools. Click on the Add Chart element in the upper left corner of the excel workbook and select more trend-line options. This feature will enable us to fit any trend-line to our data.
Select any trend line option ensuring you check the boxes; Display Equation on chart and Display R-squared value on chart.
Find the attached for the various trend-lines fitted.
The mathematical model that best fits the data is;
The quadratic model
Since it has the largest R-squared value of 1.00
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Answer:
10.75
Step-by-step explanation:
To get the average, we always SUM UP all the numbers and divide by the number of numbers.
We do this for "change" row since we want average of "change".
Let's add up all the changes:
11 + 12 + 10 + 10 + 11 + 10 + 11 = 75
How many numbers are there?
There are 7 numbers
Now, the average:
Average = Sum/Number of Numbers
Average =
The average = 10.75
Answer:
a) The formula is given by mean the margin of error. Where the margin of error is the product between the critical value from the normal standard distribution at the confidence level selected and the standard deviation for the sample mean.
b)
Step-by-step explanation:
Previous concepts
A confidence interval is "a range of values that’s likely to include a population value with a certain degree of confidence. It is often expressed a % whereby a population means lies between an upper and lower interval".
The margin of error is the range of values below and above the sample statistic in a confidence interval.
Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".
If the distribution for X is normal or if the sample size is large enough we know that the distribution for the sample mean is given by:
Part a
The formula is given by mean the margin of error. Where the margin of error is the product between the critical value from the normal standard distribution at the confidence level selected and the standard deviation for the sample mean.
Part b
The confidence interval for the mean is given by the following formula: