7. Based on the following table which indicates expenditure of the household on a commodity, answer the questions that follow ( The price of the good is Br. 10. Income, (Br. / month) 10,000 20,000 30,000 , 40,000,50,000. And Quantity Demanded, (unit/month) 50, 60, 70, 80, 90 . A) Calculate income elasticity of demand, if income increases-from Br 10,000 to Br. 20,000 and if income increases from Br.40, 000 to Br. 50.000, B) Is this a normal or an inferior or a luxury good? Justify. C) Does the proportion of household income spent on this good increase or decrease as income increases ? why ?​

Amachine purchased three years ago for $720,000 has a current book value using straight-line depreciation of $400,000: its operating expenses are $60,000 per year. a replacement machine would cost $480,000, have a useful life of nine years, and would require $26,000 per year in operating expenses. it has an expected salvage value of $130,000 after nine years. the current disposal value of the old machine is $170,000: if it is kept 9 more years, its residual value would be $20,000. calculate the total costs in keeping the old machine and purchase a new machine. should the old machine be replaced?

The company financial officer was interested in the average cost of pcs that had been purchased in the past six months. she took a random sample of the price of 10 computers, with the following results. $3,250, $1,127, $2,995, $3,250, $3,445, $3,449, $1,482, $6,120, $3,009, $4,000 what is the iqr?

One question from a survey was "how many credit cards do you currently have? " the results of the survey are provided. complete parts (a) through (g) below. click the icon to view the survey results. (a) determine the mean number of credit cards based on the raw data. the mean is 3.113.11 credit cards. (type an integer or a decimal. do not round.) (b) determine the standard deviation number of credit cards based on the raw data. the standard deviation is 1.9111.911 credit cards. (round to three decimal places as needed.) (c) determine a probability distribution for the random variable, x, the number of credit cards issued to an individual. x (# of cards) p(x) x (# of cards) p(x) 1 0.280.28 6 nothing 2 nothing 7 nothing 3 nothing 8 nothing 4 nothing 9 nothing 5 nothing 10 nothing (type integers or decimals. do not round.)