1. What is the response variable? evening high tide levels 2. What is the regression line equation? (Round each value to the nearest hundredth, if necessary.) y = 3. We can expect the PM high tide on January 4 to be approximately feet. (Round to the nearest tenth, if necessary.) This is an example of X <
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The following data are the morning and evening high tide levels for Charleston, SC from January 1-14,2017. The information for the PM high tide for January 4 is missing. Create a
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- The heights and weights of a set of students were recorded on a scatter graph. Describe the correlation depicted below: Select- strong, moderate, weak and Select- positive, negativeListed. below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross if its budget is $115 million. Use a significance level of a = 0.05. Budget ($)in Millions Gross ($) in Millions 41 21 114 68 79 51 118 65 9. 61 122 21 15 151 110 119 11 107 56 128 116 101 107 55 105 222 39 22 283 45 Click the icon to view the critical values of the Pearson correlation coefficient r. The regression equation is y%= X. %3D (Round to one decimal place as needed.)Solve for the slope, y-intercept, equation of the trend line, the correlation coefficient, and the coefficient of determination for the following the data set. Show your work and explain the steps you used to solve. Round your answer to the nearest hundredth.
- Please Answer Questions A through C. Correlation table is provided.Given the scatter plot shown, determine if the correlation is positive, negative, or if there is no relative correlation. Correlation for this scatter plot: Select an answerJim and Larry run a soup stand. The data below represents the sales of soup that they had on 8 randomly selected days, along with the high temperature on that day. a) Create a scatter diagram for this data set and comment on whether there is a positive or negative relationship between these variables.b) Calculate the correlation coefficient between temperature and sales.c) Does a linear relationship exist between these variables? Explain to me why or why not this is the case.d) Using excel, calculate the least squares regression equation for this data set. e) Using your equation, predict the soup sales on a day where the temperature is 29 degrees.f) Interpret the slope of this equation.g) Can we use this data set and regression equation to predict the sales on a day when the average temperature is 102 degrees? Why or why not?h) What is the R-squared for this equation? How do you interpret that R-squared?
- An economist wants to determine whether there is a linear relationship between a country's gross domestic product (GDP) and carbon dioxide emissions. The data are shown in the table below. c. Compute and interpret the correlation coefficient. d. Compute and interpret the coefficient of determination. e. Test for the significance of the linear relationship. Use a 0.05 level of significance. State your conclusion. Hint: Your conclusion is either of the following. • There is a significant linear relationship between a country's gross domestic product (GDP) and carbon dioxide emissions. • There is no significant linear relationship between a country's gross domestic product (GDP) and carbon dioxide emissions. GDP 1.6 3.6 4.9 1.1 0.9 2.9 2.7 2.3 1.6 1.5 (trillion dollars) Carbon Dioxide Emissions 428.2 828.8 1214.2 444.6 264 415.3 571.8 454.9 358.7 573.5 (millions of metric tons)Based on the given scatter diagram, choose the correct statement. a. It is a positive correlation. The more time an individual spends running, the higher their body fat tends to be. b. It is a positive correlation. The more time an individual spends running, the lower their body fat tends to be. c. It is a negative correlation. The more time an individual spends running, the higher their body fat tends to be. d. It is a no correlation. The amount of time an individual spends running has no correlation with his/her body fat tends to be. e. It is a negative correlation. The more time an individual spends running, the lower their body fat tends to be.Use a graphing calculator to create a scatter plot and find the line of best fit and the correlation coefficient for the following data. Round to the nearest hundredth. X 2 4 6 8124 10 Part: 0/2 y 2 3 6 7 10 15 19
- Please follow and copy the solution given in the example for the answer Thanks.The accompanying table lists the ages of acting award winners matched by the years in which the awards were won. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Should we expect that there would be a correlation? Use a significance level of a = 0.01. Click the icon to view the ages of the award winners. Construct a scatterplot. Choose the correct graph below. OA 70- 20- 20 70 Best Actress (years) B. 70- 20- 20 70 Best Actress (years) The linear correlation coefficient is r = (Round to three decimal places as needed.) 70- 20- 20 70 Best Actress (years) Q G D. 70- 20- 20 70 Best Actress (years)Based on the image attached, it shows a scatterplot of daily coffee consumption vs. IQ level. Based on the given scatter diagram, choose the correct statement. a. It is a no correlation. The amount of an individual consumes daily consumption has no correlation with his/her IQ level. b. It is a positive correlation. The more amount of an individual consumes daily consumption, the lower their IQ level to be. c. It is a negative correlation. The more amount of an individual consumes daily consumption, the lower their IQ level to be. d. It is a negative correlation. The more amount of an individual consumes daily consumption, the higher their IQ level to be. e. It is a positive correlation. The more amount of an individual consumes daily consumption, the higher their IQ level to be.