What is the t-critical value at alpha 0.05? Report your results and
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What is the t-critical value at alpha 0.05? Report your results and state your conclusions.
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- The picture shows that the estimation of the model with quarterly car sales in the U.S. from 1975 to 1990. Based on the parameter estimates, what is the predicted effect of a 10% increase in price on the number of cars sold? What would be the effect of that price increase on the value of car sales?Heights (cm) and weights (kg) are measured for 100 randomly selected adult males, and range from heights of 138 to 187 cm and weights of 40 to 150 kg. Let the predictor variable x be the first variable given. The 100 paired measurements yield x=167.94 cm, y=81.54 kg, r=0.261, P value=0.009, and y=−102+1.03x. Find the best predicted value of y (weight) given an adult male who is 181 cm tall. Use a 0.10 significance level.Heights (cm) and weights (kg) are measured for 100 randomly selected adult males, and range from heights of 135 to 188 cm and weights of 39 to 150 kg. Let the variable x be the height. The 100 paired measurements yield x=167.08 cm, y=81.32 kg, r=0.254, and y=−109+1.07x. Find the best predicted value of y (weight) given an adult male who is 163 cm tall. Use a 0.05 significance level. The best predicted value of y for an adult male who is 163 cm tall is kg. (Round to two decimal places as needed.)
- B4Please help on my assignment. ThanksHeights (cm) and weights (kg) are measured for 100 randomly selected adult males, and range from heights of 139 to 189 cm and weights of 39 to 150 kg. Let the predictor variable x be the first variable given. The 100 paired measurements yield x=167.70 cm, y=81.43 kg, r=0.324, P-value=0.001, and y=−101+1.06x. Find the best predicted value of y (weight) given an adult male who is 151 cm tall. Use a 0.10 significance level. Question content area bottom Part 1 The best predicted value of y for an adult male who is 151 cm tall is enter your response here kg. (Round to two decimal places as needed.)
- The US government is interested in understanding what predicts death rates. They have a set of data that includes the number of deaths in each state, the number of deaths resulting from vehicle accidents (VEHICLE), the number of people dying from diabetes (DIABETES), the number of deaths related to the flu (FLU) and the number of homicide deaths (HOMICIDE). Your run a regression to predict deaths and get the following output: At α = .10, which variable(s) is/are significant predictors of deaths?J 2The image shows the estimation of the model with quarterly car sales in the U.S. from 1975 to 1990. Based on the parameter estimates, what is the predicted effect of a 10% increase in price on the number of cars sold? What would be the effect of that price increase on the value of car sales?
- Heights (cm) and weights (kg) are measured for 100 randomly selected adult males, and range from heights of 139 to 188 cm and weights of 38 to 150 kg. Let the predictor variable x be the first variable given. The 100 paired measurements yield x = 167.62 cm, y = 81.37 kg, r 0.113, P-value = 0.263, and y = - 105+1.01x. Find the best predicted value of y (weight) given an adult male who is 142 cm tall. Use a 0.05 significance level. %3D The best predicted value of y for an adult male who is 142 cm tall is kg. (Round to two decimal places as needed.)Please calculate the following Chi Square equations. 1. Chi Square Single Sample Physical activity generally declines when students leave high school and enroll in college. This suggests that college is an ideal setting to promote physical activity. One study examined the level of physical activity in a sample of 570 college students. Use the hypothesis steps provided in the video to determine whether there is a significant difference in physical activity among college students. State whether you reject or fail to reject the null hypothesis.A number of studies have shown lichens (certain plants composed of an alga and a fungus) to be excellent bio-indicators of air pollution. An article gives the following data (n = 13) on x = NO3- wet deposition (g N/m²) and y = lichen (% dry weight): x 0.05 0.10 0.11 0.12 0.31 0.37 0.42 0.58 0.68 0.68 0.73 0.85 0.92 y 0.53 0.58 0.45 0.54 0.57 0.53 1.03 0.89 0.90 1.02 0.91 1.00 1.66 Predictor Constant no3 depo Estimate 0.39329 0.9286 0.1767 S = 0.1866 R-sq = 71.5% Standard Error 0.09566 t Stat 4.11 5.26 p-value 0.002 0.000 R-sq (adj) = 68.9% (a) What are the least square estimates of B and ẞ₁? (Round your answers to three decimal places.) bo = = (b) What is the margin of error for a 95% CI for ẞ₁? (Round your answer to four decimal places.) Margin of Error = (c) Predict lichen N for an NO3 - deposition value of 0.7. (Round your answer to three decimal places.) % dry weight (d) What is the estimate of σ? (Round your answer to four decimal places.) S = % dry weight