# math

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1. Calculate the descriptive statistics (summary statistics) for total sales (in K units). Show the Descriptive Statistics as your output on the Excel sheet.

2. Using the unit data by product line, compile a breakdown of sales by product line.
What percentage of the total sales is for each product line?
Also, currently the sales total equals 528,000 units.
If the sales total was changed to 100,000 total units, how many units will Alpha, Beta, and Gamma have?

3. ThermoStar tests thermostats so they are calibrated with a mean of 70 degrees, with an associated standard deviation of 2 degrees. Given this mean and standard deviation what percentage of thermostats will test below the inspector’s cutoff value and thus need to be recalibrated? (See the data sheet for the cutoff and assume that the test results are normally distributed.)

4. A sample of 40 employees shows the mean time spent in training per year to be 40 hours, with the associated standard deviation as noted in the datasheet. Construct a 95 percent confidence interval around the mean presenting both the upper and lower limits

5. We want to predict total costs, and we know the number of units produced. Do a simple linear regression to predict the total costs. What is your dependent variable? What is your independent variable? Write the regression equation showing the relationship between the independent and dependent variables. Also, use the R2 and t-statistic to tell me if this model is suitable for business decision making? If so, why? If not, why not? (Hint: copy and paste special, transpose the data into columns, then run the regression tool.)
"

• math -

Tonya took out a loan to help pay for her house. She borrowed \$70,000 for 15 years at a yearly simple interest rate of 5%. How much interest will she end up paying the bank?

• math -

Simple Interest(I) = PRT

Principal(P)- \$70,000
Rate of Interest(R)- 5%= 5/100= 0.05
Time(T)- 15 years

I=P*R*T
I= 70000*0.05*15
I= \$52500

She will pay interest of \$52500

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