I need help on C, E, F and GPlease help if you can TE+webassign.net/web/Student/Assignment-Responses/submit?dep=25473205&tags=autosave#question4734182_5=S E :Apps M GmailYouTubeO UTSA LoginNetflixThesaurus.comSlidesCarnival(c) Find the equation of the least squares regression line for predicting acrylamide concentration using frying time. (Round your answers to four decimal places.)ŷ =+(d) Is the slope of the least squares line positive or negative? Is this consistent with the scatterplot in part (b)?The slope is negative, and it is consistent with the observed association in the scatterplot.O The slope is positive, and it is consistent with the observed association in the scatterplot.The slope is positive, and it is not consistent with the observed association in the scatterplot.The slope is negative, and it is not consistent with the observed association in the scatterplot.(e) Do the scatterplot and the equation of the least squares regression line support the conclusion that longer frying times tend to be paired with higher acrylamide concentrations? Explain.Yes, the scatterplot and least squares regression line equation do support the researcher's conclusion that higher frying times tend to be paired with higher acrylamide concentrations. Theassociation between acrylamide concentration and frying time is negative, which indicates that longer frying times tend to result in higher acrylamide concentrations.No, the scatterplot and least squares regression line equation do not support the researcher's conclusion that higher frying times tend to be paired with higher acrylamide concentrations.The association between acrylamide concentration and frying time is positive, which indicates that longer frying times tend to result in higher acrylamide concentrations.Yes, the scatterplot and least squares regression line equation do support the researcher's conclusion that higher frying times tend to be paired with higher acrylamide concentrations. Theassociation between acrylamide concentration and frying time is positive, which indicates that longer frying times tend to result in higher acrylamide concentrations.No, the scatterplot and least squares regression line equation do not support the researcher's conclusion that higher frying times tend to be paired with higher acrylamide concentrations.The association between acrylamide concentration and frying time is negative, which indicates that longer frying times tend to result in higher acrylamide concentrations.(f) Use the regression line to predict acrylamide concentration (in micrograms per kilogram) for a frying time of 225 seconds? (Round your answer to three decimal places.)9.micrograms per kilogram(g) Would you use the least squares regression equation to predict acrylamide concentration for a frying time of 500 seconds? If so, what is the concentration?It is not advisable to use the least squares regression equation to predict the acrylamide concentration for a frying time of 500 seconds. The regression line is undefined at this value.It is advisable to use the least squares regression equation to predict the acrylamide concentration for a frying time of 500 seconds. The predicted acrylamide concentration is176.67 micrograms per kilogram.It is advisable to use the least squares regression equation to predict the acrylamide concentration for a frying time of 500 seconds. The predicted acrylamide concentration is264.01 micrograms per kilogram.It is advisable to use the least squares regression equation to predict the acrylamide concentration for a frying time of 500 seconds. The predicted acrylamide concentration is229.07 micrograms per kilogram.It is not advisable to use the least squares regression equation to predict the acrylamide concentration for a frying time of 500 seconds. The data set that was used to create the leastsquares regression line was based on frying times that vary between 150 and 300 seconds; the value 500 seconds is far outside that range of values. There is no guarantee that theobserved trend will continue as far as 500 seconds. TE+webassign.net/web/Student/Assignment-Responses/submit?dep=25473205&tags=autosave#question4734182_5=S E :Apps M GmailYouTubeUTSA LoginNetflixThesaurus.comSlidesCarnivalAcrylamide is a chemical that is sometimes found in cooked starchy foods and which is thought to increase the risk of certain kinds of cancer. The paper "A Statistical Regression Model for theEstimation of Acrylamide Concentrations in French Fries for Excess Lifetime Cancer Risk Assessment"t describes a study to investigate the effect of frying time (in seconds) and acrylamideconcentration (in micrograms per kilogram) in french fries. The data in the accompanying table are approximate values read from a graph that appeared in the paper.FryingTimeAcrylamideConcentration150155240120240195270180300135300275n USE SALT(a) If the goal is to learn how acrylamide concentration is related to frying time, which of these two variables is the response variable and which is the predictor variable?The response variable (y) is the acrylamide concentration, and the predictor variable (x) is the frying time.The response variable (y) is the frying time, and the predictor variable (x) is the acrylamide concentration.(b) Construct a scatterplot of these data. (Use the result of (a) for the choice of axis.)350300350p250300200250150200150100100150200250300350Frying Time (seconds)rylamide Concentrationicrograms per kilogram)

Note: Hi there! Thank you for posting the question. As there are multiple sub parts, according to our policy we have solved the first three sub parts. If you need help with other sub parts, please re post it separately.c. In this case frying time (x) is the independent variable and acrylamide concentration (y) is the dependent variable. Enter the data in Excel. Software procedure: Step-by-step procedure to obtain the scatterplot using EXCEL is defined as follows: Open an EXCEL file. In Excel sheet, enter x and y in columns A, and B, respectively. . Choose Insert > Scatter. Output obtained using Excel is given below: Software procedure: Step-by-step software procedure to obtain regression equation using EXCEL is defined as follows: Open an EXCEL file. In Excel sheet, enter x and y in columns A, and B, respectively. In Data, select Data Analysis and choose Regression. In Input Y Range, select $B$1:$B$7. In Input X Range, select $A$1:$A$7. Select Labels. Click OK. Output obtained using Excel is given below: The correlation coefficient is 0.3512. The regression equation is, ŷ = 89.3269 + 0.3494x. e. The correlation coefficient is positive. Yes, the scatterplot and least square regression line equation do support the researcher’s conclusion that higher frying times tend to be paired with higher acrylamide concentrations. The association between acryiamide concentration and frying time is positive, which indicates that longer frying times tend to result in higher acryiamide concentration. f. Substitute x = 225 in the regression equation. That is, ŷ = 89.3269 + 0.3494(225) = 167.942. Thus, the predicted acryiamide concentration for a frying time of 225 sounds is 167.942 micrograms per kilogram.