Enter the following table into your calculator or the Desmos Grapher and create the scatterplat1000O about 2500O about 1500O about 3000about 22002000200030003000400050007000800010000Y8 8 8 8 8 8 8 8 8 8900700800700700600500400400500Using a quadratic model, choose the best prediction for the x-value when y-750

We have to find the value of x when y= 750.First we will plot the regression and then find the value…

Answered: Enter the following table into your…

Algebra and Trigonometry (6th Edition)

6th Edition

ISBN:9780134463216

Author:Robert F. Blitzer

Publisher:Robert F. Blitzer

ChapterP: Prerequisites: Fundamental Concepts Of Algebra

Section: Chapter Questions

Problem 1MCCP: In Exercises 1-25, simplify the given expression or perform the indicated operation (and simplify,...

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As a researcher, you are interested if there is a significant difference in immunizations in those in low socioeconomic status and those in high socioeconomic status. To evaluate this you use the data below to calculate a Chi-Square (X2). Socioeconomic Status Socioeconomic Status Total High Low Immunized 1000 500 1500 Not Immunized 250 750 1000 Total 1250 1250 2500
Make a scatterplot of the untransformed data and tell which kind ofrelationship the points seem to follow. Also name the best type oftransformation needed to "straighten" the plot.Note: Part of the transformation shouId involve subtracting 1900 from the year soyou're working with more manageable numbers.Now try some transformations to get the data as close to linear as possible.(Use your calculator to transform the data, and try scatterplots of the differenttransformations). Then find the regression line, r, and r2.Tell which transformation worked the best and back it up by showing:• A scatterplot of the transformed data with the least-squares regression equation andline, r, and r-squared.• A plot of the original data with the regression equation converted to a non-linearequation
The numbers of polio cases in the world are shown in the table for various years. Year Number of Polio Cases (thousands) 1988 1992 1996 2000 2005 2007 350 138 33 3 3.2 1.3 Let f(t) be the number of polio cases (in thousands) t years after 1980. Copy the data to Desmos to draw a scatterplot of the data. Make sure to adjust the years so they represent years after 1980. a) Is it better to model the data with a linear or with an exponential model? [Select an answer b) Use regression in Desmos to find an appropriate model for f. Make sure to check Log mode in the parameter window in Desmos if you are fitting an exponential model. f(t) Round the coefficients to 4 decimal places. Hint: Use the variablet from the drop down menu when entering the equation. Do not just type in t. c) Predict the number of polio cases in 2013. d) Find the approximate half-life of the number of polio cases. Round the answer to one decimal place. years
Data in the table comes from the NASA Global Climate Change website. It gives the average globaltemperature, in Celsius, for the given year. Use both rows for your calculations. For this problem, youwill see how well year correlates with the average temperature. Let ? be the number of years since1984 and ? be the average global temperature in degrees Celsius.Year 1984 1986 1988 1990 1992 1994 1996 1998 2000Temp 0.16 0.18 0.38 0.45 0.22 0.31 0.33 0.61 0.40Year 2002 2004 2006 2008 2010 2012 2014 2016 2018Temp 0.63 0.54 0.64 0.54 0.72 0.64 0.75 1.02 0.85a. Make a scatterplot of the data. Being sure to clearly label each axis. Keep in mind howeach variable is defined. Based on this scatterplot, is a linear model reasonable for this data set?Briefly explain.b. Determine the correlation coefficient for this data. Interpret this value in context.c. Determine the coefficient of determination for this data. Interpret this value incontext.d.State the regression line for the data.e. What does the…
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Suppose that the number of tee shirts sold (N) depends linearly on the price charged (x). Write an equation showing this dependence.
Oliver and Tony work at a dentist office. They had a conversation one day about how much time it took to complete a routine cleaning for each patient. Tony wondered if the time since the last visit to the office was related to the length of a cleaning. Oliver went to the filing cabinet and came up with the following data: x = Months since last visit y = Length of cleaning (mins) 6 20 13 49 6 8 9 15 33 35 42 14 7 11 9 55 36 52 29 E SALETSTRANICZON RUSSAREN Co JINSIEMELLET

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