Activity 1:

- Look at the hypothesis test results for '1st Peer' and Explain:

1- What a type 1 error would mean in a practical sense?

- Looking at 1st Peer's outcome:

2- Is a type 1 error likely or not? What specific values indicated this?

1st peer:For my data this week (see attached) I came up with the following results. Based on week 1/2 data, my mean was $45,039.1, Standard Error: $5201.57. The 40% of my sample of vehicles was $38,228.00. Since the scenario is posed that they think a car will sell for greater than 40% of my vehicles' prices, I needed to run a right-tailed hypothesis. As part of this, I needed to use the T-test and not a Z-test. This was due to the small sample size (n=10).

My T-stat score was 1.309431 and my P-value came out to 0.111414. Now since our alpha is 0.05, my p-value is > than the alpha. This means that I can accept the null hypothesis and reject the alternative hypothesis (see data for hypothesis numbers). In other words, I would reject the claim that the average vehicle would sell for greater than 40% of my vehicle prices.

L8 V X V fx =T. DIST.RT(L7,9) E F G H L K Column1 Model Price ($) Week 6: Hypothesis Data XC60 T8 64,778 Mean 45039.1 Mean $45,039.10 XC60 B5 52,995 Standard Error 5201.568848 SE $5,201.57 Countryman John Cooper 40% of 41,000 Works w/ Storage PKG Median 40220 prices $38,228.00 Prius 34,054 Mode #N/A Accord EX-L 42,095 Standard Deviation 16448.80496 T-stat 1.309431575 8 CR-V Touring 39,440 Sample Variance 270563184.8 P-value 0.111414016 Santa Fe Blue 36,410 Kurtosis 1.184210673 10 K5 GT-Line 32,880 Skewness 1.292202562 11 Elantra SEL 26,499 Range 53741 12 Macan S 80,240 Minimum 26499 13 Maximum 80240 14 Sum 450391 15 Count 10