REGRESSION ANALYSIS: PERFORMANCE TASKIntroductionIn the study of Tingganay (2003), students stay incompetent in mathematics for they lackcompetency on the fundamental concepts comprised in the study of this discipline. In the 2012Program for International Student Assessment (PISA), United States recorded low scores in mathematicsand ranked 36th out of the 65 participants worldwide. PISA is a system of international assessments thatmeasures 15-year-olds' capabilities in basic mathematics literacy, including science and reading(Willms, 2003). According to Wilson (2000), Mathematics is not exactly known as academe's mostprogressive discipline when it comes to curricular reform. Particularly, in calculus, students are stilltaught to plug in numbers and chug through a formula, and some undergraduates never learn howthis course relates to other disciplines, much less the real world. In addition, Husch (2001), approximately40% of the students enrolled in the first semester calculus class at The University of Tennessee in fallsemester, 1999, made grades of D, F, or W (Withdrawn). As cited by Husch (2001), repeatedly, professorshave reported similar situations with high failure rates. This entails that academic performance ofstudents in Mathematics is lower than what is desired.GoalYou are tasked to determine the equation that will predict students' grades in Statistics basedon student's grades in General Mathematics. The following are reported grades of 15 randomlyselected students under the Science, Technology, Engineering and Mathematics Program enrolled inthe Academic Year 2017-2018.General Mathematics (x):888887818780928988818387898988Statistics (y):9089868086819088928084868890871. Prepare a table then compute for the coefficient of correlation.2. If a correlation exists, determine the regression equation that will predict students' grades inbasic calculus based on the students' pre-calculus grades.3. Summarize your results in the following table.VariablesМeanrRegression EquationGen MathStatistics4. Interpret the results in the table under Task Number 3.5. Using the regression equation, substitute your gen math grade (x) to predict your statistics grade(y).

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1. Prepare a table then compute for the coefficient of correlation. 2. If a correlation exists, determine the regression equation that will predict students' gro basic calculus based on the students' pre-calculus grades. 3. Summarize your results in the following table. Variables Mean r Regression Equation Gen Math Statistics

1. Prepare a table then compute for the coefficient of correlation. 2. If a correlation exists, determine the regression equation that will predict students' gro basic calculus based on the students' pre-calculus grades. 3. Summarize your results in the following table. Variables Mean r Regression Equation Gen Math Statistics

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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The linear correlation between violent crime rate and percentage of the population that has a cell phone is −0.918 for years since 1995. Do you believe that increasing the percentage of the population that has a cell phone will decrease the violent crime rate? What might be a lurking variable between percentage of the population with a cell phone and violent crime rate? Question content area bottom Part 1 Will increasing the percentage of the population that has a cell phone decrease the violent crime? Part 2 What might be a lurking variable between percentage of the population with a cell phone and violent crime rate?
Part 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.
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discuss how the coefficient of determination and the coefficient of correlation are related and how you would use them in regression analysis
Determine if correlation between the two given variables is likely to be positive or negative, or if they are not likely to display a linear relationship. Your daily calorie intake and weight. (a) Positive (b) Negative (c) No correlation
Find the regression equation, letting overhead width be the predictor (x) variable. Find the best predicted weight of a seal if the overhead width measured from a photograph is 1.7 cm. Can the prediction be correct? What is wrong with predicting the weight in this case? Use a significance level of 0.05. Overhead Width (cm) Weight (kg) Click the icon to view the critical values of the Pearson correlation coefficient r. F n example Get more help. The regression equation is y=-159.5+ 43.2 x (Round to one decimal place as needed.) 3 # The best predicted weight for an overhead width of 1.7 cm is kg. (Round to one decimal place as needed.) I 80 E 26 D 7.8 161 C $ 4 Q F4 8.3 212 R F Stv 9.9 276 07 20 V F5 T 9.1 215 G 6 B 9.7 262 746 MacBook Air FO 7.3 166 Y H & 7 N F7 U X +00 8 J DII FB - M ( 9 K O < I ) O |qqqqqqqqi L F10 Clear all P . V : ; F11 { + [ command option Check answer = ? 11 I F12 1
please answer the question and show work!! thank you also please make sure if writing on paper handwriting can be read thank you again :)
Prev The table below gives the list price and the number of bids received for five randomly selected items sold through online auctions. Using this data, consider the equation of the regression line, y = bo + b₁x, for predicting the number of bids an Item will receive based on the list price. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, In practice, It would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Price in Dollars 28 33 36 42 45 Number of Bids 1 7 8 9 10 Step 3 of 6: Find the estimated value of y when x = 33. Round your answer to three decimal places. Table Copy Data Next
Create two lists and make a scatterplot of the data and find the line-of-best-fit (regression line). For part a below, round all number values in your answer to the nearest tenth. a) What is the equation of the line-of-best-fit? ________________________ b) To the nearest thousandth, what is the value of the correlation coefficient, r ? _________ c) According to the regression equation from part a, what is the predicted salary for year 8? Round your answer to the nearest dollar. __________________
Please help, this is for financial mathematics, thank you so much!!!