1. Table C7-1 shows the weekly ticket sales of 4 competing regional airlines, including Omega Airlines. Omega thinks that probably the dispersion of data around the mean of ticket sales for the past 18 weeks are not the same for the 4 airlines.

In Excel, run descriptive statistics on the variables (each airline) in Table C7-1 to find the mean, median, standard deviation, range, and maximumfor each airline's sales. Find the overall mean of sales for all 4airlines (we'll call that the Overall Mean... this is our )and overall standarddeviation (this is our ).

Run a test of ANOVA on the data at 95% confidence to determine if there is a significant difference in variance around the mean of sales by airline[if you are using Excel, use "ANOVA: single factor";If you are using Jamovi (recommended), use "ANOVA", andthen copy and paste your output into your Excel file]. Highlight the F-statistic, and the p-value in your output; and interpret the results in a sentence articulating the F and p-value to answer the question of whether or not sales are significantly different by airline (is there an airline that Omega Airlines should benchmark?)

c.Forecast Omega's ticket sales for Week 19 using a 4-week moving average, weighted moving average (choose your own weights based on what you see in the data), exponential smoothing (choose your own alpha based on what you see in the data), and regression analysis. Find the Mean Absolute Deviation for each of these and then highlight the forecast that is associated with the most accurate method. In your Excel file, include a sentence articulating this("Comparison of 4 statistical forecasting methods provides evidence to suggest that [method x]is most accurate with a MAD of [x amount] from actual sales; therefore, we forecast demand in Week 19 to be approximately [x dollars of ticketsales].")

Table C7-1: Demand (ticket sales) by Airline First 18 Weeks of 2022 ($ thousands)
Week	V-West	JJA	All-Ways	Omega
1	980	555	687	699
2	955	558	610	694
3	920	470	605	645
4	910	451	695	613
5	901	411	703	624
6	986	491	591	667
7	915	477	651	719
8	961	411	708	730
9	905	520	707	754
10	840	499	721	798
11	892	501	597	810
12	888	523	623	794
13	959	584	627	777
14	970	583	625	730
15	963	591	611	720
16	981	595	618	724
17	964	599	603	721
18	979	608	582	719