business analysis exam 2
Based on the equation Y = 4.29 + 143.3X, Sales(Y) is in Units of $1000.00 and Advertising(X) is in Units of $100. What are Sales when $2,126.00 is spent on advertising?
((x/100) * m + b) * 1000 EXAMPLE: 2637/100 = (26.37)(143.3) = 3,778.821 + 4.29 = 3783.111(1000) = 3,783,111
Using the data below, what is the simple exponential smoothing forecast for the 4th week where α=0.4?
(0.4 * tsv of previous week) + ( 1-0.4 * forecast of previous week) do for third and fourth week and fourth week is answer EXAMPLE: week - tsv 1 - 6 2 - 4 3 - 8 4 - 4 (0.4 * 4) + (0.6 * 6) = 5.52 (0.4 * 8) + (0.6 * 5.52) = 6.3 =6.3
Based on the above chart and assuming that without seasonality each quarter will have equal demand: The Seasonal Index for QT1 is
(Q1 + Q2 + Q3 + Q4) / 4 = X ; Q1 / X EXAMPLE: quarter - actual quarterly sales 1 - 156 2 - 180 3 - 255 4 - 230 (156 + 180 + 255 + 230) / 4 = 205.25 156/ 205.25 = 0.76
Based on the above chart and assuming that without seasonality each quarter will have equal demand: The Seasonal Index for QT3 is
(Q1 + Q2 + Q3 + Q4) / 4 = X ; Q3 / X EXAMPLE: quarter - actual quarterly sales 1 - 139 2 - 160 3 - 244 4 - 250 (139 + 160 + 244 + 250) / 4 = 198.25 244/ 198.25 = 1.23
Using the data below, what is the weighted moving average forecast for the 4th week? The weights are .20, .30, .50 (oldest period to most recent period)
(WT 1 * week 1) + (WT 2 * week 2) + (WT 3 * week 3) EXAMPLE: week - tsv 1 - 20 2 - 20 3 - 15 4 - 15 (.20 * 20) + (.30 * 20) + (.50 * 15) = 17.5
Using the data below and the SES forecast α=0.3 , what is the error for the 3rd week?
(a)(previous period) + (1-a)(previous forecast EXAMPLE: week - tsv 1 - 15 2 - 5 3 - 24 4 - 15 (.3)(5) + (.7)(15) = 12
Using the data below, calculate the squared error for the 4th week. Use the 2 period moving average to create the forecast.
(average of 2nd and 3rd week - week 4)^2 EXAMPLE: week - tsv 1 - 9 2 - 11 3 - 6 4 - 17 (11 + 6)/ 2 = - 8.5 - 17 = -8.5^2 = 72.3
Using the data below, what is the 2 period moving average forecast for the 3rd week?
(period 1 + period 2)/2 EXAMPLE: week - tsv 1 - 9 2 - 25 3 - 24 4 - 11 (9 + 25)/2 = 17
Using the data below, what is the 3 period moving average forecast for the 4th week?
(week 1 + week 2 + week 3) / 3 EXAMPLE: week - tsv 1 - 25 2 - 7 3 - 19 4 - 18 (25+7+19) / 3 = 17 *literally just the average of first three weeks*
Using the data below, calculate the absolute error for the 3rd week. Use the 2 period moving average to create the forecast
(week 1 + week 2)/ 2 - week 3 EXAMPLE: week - tsv 1 - 18 2 - 8 3 - 9 4 - 24 (18 + 8)/ 2 = 13 - 9 = 4
R^2 can take value from?
0 to 1
Interpret the line, Y=5X+6
5 is the Slope
What is regression analysis?
A statistical process for estimating the relationships among variables
Which of the following is NOT a type of Qualitative forecasting?
Heuristic
When we have many independent variables which we use to predict the dependent variable, we call this process as?
Multiple Regression
The formula of slope(M) in the equation Y=MX+B is?
Rise/Run
The Monthly indexes for the first 12 months are: 1.25, 1.25, 1, 1, .75, .75, .7, .8, .8, 0.66, 1.08. What is the index for the last month?
X + X + X + X + X + X + X + X + X + X + X - 12 EXAMPLE: 1.25 + 1.25 + 1 + 1 + .75 + .75 + .7 + .8 + .8 + 0.66 + 1.08 - 12 = 1.96
A bias of -10 means
You are over forecasting
Using the data below and the Naïve forecast, what is the error calculation for the 3rd week?
actual - forecast = error calculation EXAMPLE: week - tsv 1 - 15 2 - 10 3 - 23 4 - 18 23-10=13 (if happened to be negative include negative sign in answer)
If the actual sales are 2,319.00 units and the seasonal index for this period is 1.04, find the deseasonalized sales for this period?
actual sales / seasonal index EXAMPLE: 1029 / 1.80 = 571.67
The deseasonalized sales for this period when the actual sales are 2,268.00 units and the seasonal index for this period is 1.44?
actual sales / seasonal index EXAMPLE: 2268 / 1.44 = 1575
Interpret coefficient -6 from the regression equation: y = 100 - 6X where y is number of donuts sold and x is price. So on an average, if price increases by one dollar, the number of donuts sold
decreases by 6
Based on the below data what is the regression equation?
mx= advertising coefficient b= intercept coefficient EXAMPLE: intercept = 3 advertising = 32 3 + 32x
Based on the below data what will be the value of standard error?
sqrt(residual ms) *aka mse* EXAMPLE: regression ms = 3.33 sqrt(3.33) = 1.82
Using the data below, what is the value of RMSE?
sqrt(sum of error^2/ # of observations) EXAMPLE: week - tsv - forecast 1 - 3 - 5 2 - 5 - 4 3 - 2 - 7 4 - 8 - 6 error (subract across tsv and forecast) 2 1 5 2 error^2 4 1 25 4 =34 sqrt(34/4) = 2.92
Using the data below, what is the value of MAD?
sum of absolute deviations/ # of observations sum of absolute deviations= tsv-forecast EXAMPLE: week - tsv - forecast 1 - 6 - 5 2 - 5 - 4 3 - 4 - 4 4 - 7 - 8 abs deviation (subtract across tsv and forecast) 1 1 0 1 =3/4 = .75
The sales trend has been modeled as: Sales=3.00 * t + 100.00, where t = time in quarters, beginning in Q1 2015. Seasonality for the four quarterly periods is given in the table below. Find the seasonalized forecast for Q1 of 2017
to find t count how many quarters are between the first and last quarter then plug into 3.00 * t + 100 and solve then multiply answer by seasonal factor of desired quarter EXAMPLE: quarter - seasonal factor 1 - 1.1 2 - 0.9 3 - 0.9 4 - 9 quarters from Q1 2015 to Q1 2017 3.00 (9) + 100 = 127 (1.1) = 139.7
Find the seasonalized forecast for Q2 of 2017.The sales trend has been modeled as: Sales = 2 * t + 200, where t= time in quarters, beginning in Q1 2014. Seasonality for the four quarterly periods is given in the table below.
to find t count how many quarters are between the first and last quarter then plug into 3.00 * t + 100 and solve then multiply answer by seasonal factor of desired quarter EXAMPLE: quarter - seasonal factor 1 - 1.2 2 - 0.97 3 - 0.5 4 - 14 quarters from Q1 2014 to Q2 2017 2 (14) + 200 = 228 (0.97) = 221.2
Sales(Y) is in Units of $1000.00 and Advertising(X) is in Units of $100. If we want to calculate the value of sales when $32,220.00 is spent on advertising. What do we use for X in the following equation? Y=42.9+143.3X.
x/100 EXAMPLE: 32,220/100 = 322.20
