ContextGosset's Seed Plot DataWilliam S. Gosset was employed by the Guinness brewing company of Dublin. Sample sizes available for experimentation in brewing were necessarily small. At that time, Gosset contacted a famous statistician Karl Pearson (1857-1936) and was told that there were no techniques for developing probability models for small data sets. Gosset studied under Pearson, and the outcome of his study was perhaps the most famous paper in statistical literature, "The Probable Error of a Mean" (1908), which introduced the T-distribution.Since Gosset was employed by Guinness, any work he produced would be owned by Guinness, so he published under a pseudonym, "Student"; hence, the T-distribution is often referred to as Student's T-distribution.To illustrate his analysis, Gosset used the results of seeding 11 different plots of land with two different types of seed: regular and kiln-dried. He wanted to determine if drying seeds before planting increased plant yield. Since different plots of soil may be naturally more fertile, this confounding variable was eliminated by using the matched pairs design and planting both types of seed in all 11 plots.The resulting data (corn yield in pounds per acre) are as follows.PlotRegular seedKiln-dried Seed11903200921935191531910201142496246352108218061961192572060212281444148291612154210131614431115111535We use these data to test the hypothesis that kiln-dried seed yields more corn than regular seed.Because of the nature of the experimental design (matched pairs), we are testing the difference in yield.PlotRegular seedKiln-dried SeedDifference119032009–10621935191520319102011–10142496246333521082180–7261961192536720602122–62814441482–38916121542701013161443–1271115111535–24Note that the differences were calculated: regular − kiln-dried.VariablesRegular seed: regular seeds that were traditionally used for plantingkiln-dried: seed that were kiln-dried before plantingDataDownload the seed (Links to an external site.) data file, and then upload the file into StatCrunch. PromptState the hypotheses and define the parameter.Checking conditions: Since Gosset invented the T-distribution, we will assume that his sample meets the conditions and proceed with the T-test. Regardless, answer these questions to demonstrate your understanding of the conditions for use of the T-model.But first you will need to review the dotplots for the data (opens in a new tab). Which graph is used to check conditions? Why?What do we look for in the graph to verify that conditions are met?What else do we need to know about the sample of seeds before using the T-test?Use StatCrunch to find the T-score and the P-value. Hint: as you work through the StatCrunch directions, keep in mind that we want to calculate the differences as regular − kiln-dried . So you will choose Regular seed for Sample 1 and kiln-dried seed for Sample 2. (directions)Copy and paste the information in the StatCrunch output window into your initial post.State a conclusion based on the context of this scenario.

Which best describes the correlation of the data.Positive correlationNegative correlationRelatively no correlationScattered correlation===============================Which best describes the correlation of the graph.Positive correlationNegative correlationRelatively no correlationScattered correlation=======================Which situation describes a negative correlation?The number of miles driven and the amount of gas used.The number of gallons of gas purchased and the amount paid for the gas.The size of a car’s gas tank and the number of gallons it holds.The number of miles driven and the amount of gas left in the gas tank.=====================Based on the line of best fit drawn below, which value could be expected for the data in June 2015?230310480540==================Which equation best models the data in the scatter plot?y=15=====================Using the scatter plot and line of best fit below, predict the average number of hours slept when 5 hours are spent watching TV.5 hours4 hours2 hours9 hours=====================Use the data below to draw a scatter plot. Then, decide which equation is the best approximation of the best-fitting line.y = -2x + 2.5y = 1.2x - 7.3y = -0.7x + 2.7y = -1.1x + 2.3=====================Which two points would be best to you use to find the equation of the best-fitting line shown on the scatter plot below?(0, 10.5) and (4.5, 6.5)(3.9, 9.5) and (8.7, 2.5)(0, 12) and (10.5, 0)(7, 4) and (0, 12)======================Which of the following shows the best approximation of a best fit line for the data below?======================A contractor recorded the amount of money earned for different jobs and the amount of time spent on each job. The data are shown in the scatterplot below. Based on the data, predict the amount of money the carpenter would earn from a job that took 15 days to complete.$1500$3000$3500$1000====================