There is a positive relationship between how frequently households shop at a certain mall and the distance they live from that mall. Match the type of Hypothesis to the correct equation. slope = 0 1. Null Hypothesis slope > 0 2. Research Hypothesis >
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- We expect a car's highway gas mileage to be related to its city gas mileage (in miles per gallon, mpg). Data for all 1259 vehicles in the government's 2019 Fuel Economy Guide give the regression line highway mpg = 8.720 + (0.914x city mpg) for predicting highway mileage from city mileage. 1 O Macmillan Learning (b) What is the intercept? Give your answer to three decimal places. intercept: Why is the value of the intercept not statistically meaningful? The value of the intercept is an average value calculated from a sample. The value of the intercept represents the predicted highway mileage for city gas mileage of 0 mpg, and such a prediction would be invalid since 0 is outside the range of the data. The value of the intercept represents the predicted highway mileage for slope 0. O The value of the intercept represents the predicted city mileage for highway gas mileage of 0 mpg, and such a car does not exist. mpgThe following linear regression model can be used to predict ticket sales at a popular water park. Ticket sales per hour = - 631.25 + 11.25(current temperature in °F)23) Choose the statement that best states the meaning of the slope in this context. A) The slope tells us that a one degree increase in temperature is associated with an average increase in ticket sales of 11.25 tickets. B) The slope tells us that high temperatures are causing more people to buy tickets to the water park. C) The slope tells us that if ticket sales are decreasing there must have been a drop in temperature. D) None of thesePart 2: Regression Based on the correlation you ran to assess the relationship between # of exposures and perceived connection strength recalled, please carry out the steps to determine the equation for the regression line (or best-fitting line) а. Step 1: find the slope and y-intercept b. Step 2: Using these values, write the equation for the best fitting line, but make sure to write it in terms of the specific predictor (X) and predicted (Y) variables of interest. In other words, your equation should use variable names “# of exposures" and "perceived strength of connection rating", rather than X and Y. Using the regression equation, please predict the perceived connection strength score for a student exposed subliminally to the stranger's face seven times. Make sure to show your work с. d. Using the regression equation, draw the line of best fit on your scatterplot. Please use at least 3 points to anchor your line and show your work.
- Think of two variables, they could be from everyday life, that you feel would be strongly correlated, either positively or negatively. Describe why you would care about those two variables being correlated, and if you were to find a linear equation (best fit line) for them, what would you use it for. If you need to do some research online to find examples to post, that would be encouraged. 1.) Describe why these variables/correlation have personal meaning in your life 2.) Note whether they have a positive or negative correlation 3.) Describe what the best fit regression line would representNote:- Do not provide handwritten solution. Maintain accuracy and quality in your answer. Take care of plagiarism. Answer completely. You will get up vote for sure.Using your favorite statistics software package, you generate a scatter plot with a regression equation and correlation coefficient. The regression equation is reported asy=−71.07x+16.92y=-71.07x+16.92and the r=−0.52r=-0.52.What percentage of the variation in y can be explained by the variation in the values of x?r² = % (Report exact answer, and do not enter the % sign)
- I’m taking a probability and statistics class please get this correct because I’ve gotten wrong answers beforePlease define all variables and do all parts.3. Marge aims to find out whether income predicts life satisfaction in any way. She assesses income and life satisfaction in 30 citizens of Springfield. Her calculations result in a slope b = 2.2 and an SE = 0.4. Can she conclude that income significantly predicts life satisfaction on the 5% level? . HO: B=0 H1: ẞ#0
- Range of ankle motion is a contributing factor to falls among the elderly. Suppose a team of researchers is studying how compression hosiery, typical shoes, and medical shoes affect range of ankle motion. In particular, note the variables Barefoot and Footwear2. Barefoot represents a subject's range of ankle motion (in degrees) while barefoot, and Footwear2 represents their range of ankle motion (in degrees) while wearing medical shoes. Use this data and your preferred software to calculate the equation of the least-squares linear regression line to predict a subject's range of ankle motion while wearing medical shoes, ?̂ , based on their range of ankle motion while barefoot, ? . Round your coefficients to two decimal places of precision. ?̂ = A physical therapist determines that her patient Jan has a range of ankle motion of 7.26°7.26° while barefoot. Predict Jan's range of ankle motion while wearing medical shoes, ?̂ . Round your answer to two decimal places. ?̂ = Suppose Jan's…Answer number one onlyA multiple regression analysis has more than onea. Fixed costsb. Dependent variablec. independent variabled. both fixed costs and dependent variable