A manufacturing plant makes two different types of products. Product A has a profit of $50 and product B has a profit of $60. Product A requires 10 hours of labor and product B requires 12 hours of labor. Product A requires 20 KWs of power to make, while Product B requires 10 KWs of power to make. The plant cannot make more than 30 of product B each month due to market saturation. There are a total of 900 labor hours and a total of 1000 KW of power available each month. A manufacturing process is suspected to be affected by the level of humidity. Humidity and scrap data was taken on several days. Required:
a. Use the least squares regression method to determine a prediction equation for the data.
b. Determine the equation first by using matrix calculations and then using the regression data analysis tool. What is the r squared value? The company would like to know what would happen to the scrap level if the level of humidity level reaches 0.60 (60%). Is the model a good indicator of the effects of humidity on scrap?

He moto hotel opened for business on may 1, 2017. here is its trial balance before adjustment on may 31. moto hotel trial balance may 31, 2017 debit credit cash $ 2,283 supplies 2,600 prepaid insurance 1,800 land 14,783 buildings 72,400 equipment 16,800 accounts payable $ 4,483 unearned rent revenue 3,300 mortgage payable 38,400 common stock 59,783 rent revenue 9,000 salaries and wages expense 3,000 utilities expense 800 advertising expense 500 $114,966 $114,966 other data: 1. insurance expires at the rate of $360 per month. 2. a count of supplies shows $1,050 of unused supplies on may 31. 3. (a) annual depreciation is $2,760 on the building. (b) annual depreciation is $2,160 on equipment. 4. the mortgage interest rate is 5%. (the mortgage was taken out on may 1.) 5. unearned rent of $2,580 has been earned. 6. salaries of $810 are accrued and unpaid at may 31

The answer here, x=7, is not in the interval that you selected in the previous part. what is wrong with the work shown above?

Ido not understand this project overview agricultural commodities are bought and sold through the stock exchange. the price of commodities changes all the time. investors buy many agricultural commodities before they are ready for shipping. when an investor buys an agricultural commodity that is going to be ready in the future, they call this purchasing futures. this might be a future crop, meat that has not yet been processed, or another type of agricultural commodity. for this project, you will have to decide how to spend $10,000. research the new york stock exchange. find one or more agricultural commodities that you are interested in. remember, it may be listed as a future crop. instructions identify the agricultural commodities that you think have the best chance of going up in price. think about what is going on with supply and demand. decide how you will spend your money. you may purchase only agricultural commodities. check the market every day for a week. record the price of your commodity or commodities each day. you may buy or sell your commodities at any time during the week. you may sell your commodities and buy different ones. feel free to experiment with the $10,000 by buying and selling commodities, but make sure to keep a careful record of your activities. at the end of the week, you will write a report on your investments. this report should be structured to include this information: page 1: explain how the stock market works. page 2: list all commodities purchased. describe each in detail. discuss why you selected these commodities. remember, they must be agricultural. page 3: create a chart or graph to illustrate the price of your commodity or commodities over the week’s time. list all of your activity buying and selling. make sure you include prices and details. page 4: write a summary of your experience. describe what you might do differently if you were using actual money. propose potential reasons why the price of each commodity may go up or down.