V. Make the best Prediction for Total Defense Spending in the year 2006 3) NORMA

Question

V. Make the best Prediction for Total Defense Spending in the year 2006 3) NORMALITY ASSESMENT In future chapters we will use statistical methods that require the sample data to come from a population with normal distribution. Since population data is most of the time immeasurable (due to the size and/or lack of resources) we cannot be sure that the population is normally distributed. We must obtain a sample and learn how to conclude if the sample comes from a normally distributed population or not. For this, read carefully page 291-292 about Assessing Normality Since our sample size is small, a histogram will not be very helpful in revealing the distribution of the data. Instead, we will also assume that there are no outliers on the given data and we will just use the Normal Quantile Plot to make our conclusions. EXCEL can be used to generate a NORMAL QUANTILE PLOT for the sample data (see Video for Excel Instructions). For Measurements Calculations (letter c and d), use your TI30XIIS calculator and you must use same rounding rules as indicated in class and do not forget the units. . Ross gathered a sample of braking distances (in feet) measured under standard conditions for a sample of large cars: 139, 134, 145, 143, 131 Create a normal quantile plot. b) Does the sample of braking distances (in feet) appear to come from a normally distributed population? Explain in detail how you got to your conclusion using the above result. c) Find the four measurements of center for the sample of braking distances. d Find the three measurements of variation for the sample of braking distances. Tom randomly selects flights and the times (minutes) required to taxi out for takeoff were measured:

Explanation / Answer

> #c
> mean(x)
[1] 138.4
> median(x)
[1] 139
> mode(x)
[1] "numeric"
> mean(range(x))
[1] 138
> #d
> sd(x)
[1] 5.899152
> range(x)
[1] 131 145
> var(x)
[1] 34.8

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