For this study, we were trying to describe Bayes, Gauss or Nightingale cars data. We did not have enough prior information to hypothesize that one was faster than then other. We have access to data for the finishing time (in seconds) from racing each car on the ovel track. The class was divided into three groups and each group started run cars in different orders..

Data was collected and entered into an excel sheet, which was then utilized to evaluate the data in this study.

In this project, we will analyze average finishing times of each automobile to see if there are any differences in average speed and, if so, which car body type is faster.

First, describe the types of variables found in the data set, their names, and whether they are categorical or numerical, as well as the units and sample size.

Plots such as bar plots for average car speeds, box plots for car data with five-number summaries, and plot histograms are all attached here.

Explain the difference between a histogram and a box plot.

Starting with some introductory words about graphs is a good place to start.

Something along these lines could work.

The bar graphs that follow help us visualize the differences in racing speeds.

This is where the graph will be placed.

Explain what you've seen and any conclusions you've reached.

Distribution shapes and any initial guesses

Here is the car's box plot; describe what you've seen, including any symmetry, outliers, and any reasons for the distribution's shape.

Figure 2 is a diagram.

Explain your plots, including the x and y axes and what you saw on them.

Data in numerical form:

Complete the following table with the sample size, mean, median, maximum, minimum, and standard deviation for your class data.

Please let us know if you notice any anomalies.

Write a paragraph describing the variables you chose to use to determine which car is faster based on the Finishing Time variable.

Words and tables should both be included.

Table 1. Summary Statistics for ________________Put variable name here - be sure to include the units. ___.,

N Mean St. Dev. Bayes Gauess NightingaleName ssneg Bayes Nightingale MC 21.88 23.03 24.01 DL 21.71 23.09 23.6 JZ 27.76 23.67 23.82 AA 35.8 24.8 24.43 NH 23.4 23.56 24.4 JM 26.7 22.49 23.9 AA 16.6 23.3 18.16 ZM 25.35 23.15 25.08 DM 21.96 24.38 26.9 AG 21.96 23.2 24.1 SRR 36.41 26 31.67 Su 22.38 23.86 24.75 Nick 21.78 23.41 23.76 Justin 35.96 32.99 27.9 Dennis 30.13 25.05 24.61 Narayan 21.6 22.95 23.59 Brian 23.44 28.15 23.89 Omar 21.94 24.27 24.09 phi 21.61 23.65 23.79 Dex 21.63 22.97 24.08 cha 21.67 23.29 24.14 Nic 22.08 25.31 25.18 Abe 21.59 23.64 23.57 tre 21.85 24.05 23.7 sar 24.19 26.38 24.32