Excel Data and Worksheet for Assignment 9- Due 11192023

Assignment # 9 - For full credit, submit BOTH this template worksheet ( worth # 2 ( Chi-square, Goodness-of-Fit test ( similar to the Try-It problem # 11.2 of the Open St a) Hypotheses: Null: Students do homework equally throughout the week, and they fit a uniform distr Alternative: Students do not do homework equally throughout the week, and they do not fit if n =105 and uniform, Differences Day Observed Values ( O ) Expected Values ( E ) O-E Number Sunday 32 15 17 per day Monday 4 15 -11 Tuesday 7 15 -8 Wednesday 9 15 -6 df = 6 Thursday 12 15 -3 Friday 16 15 1 Saturday 25 15 10 and then your p-value use the CHISQ.DIST.RT function NOTE: "X" is your Sum from the table above NOTE: Deg_freedom = n-1 p-value = would expect = 105/7 = 15 per day b) Calculate your chi-square X 2 statistic

c) Make a Decision ( compare your p-value with your pre-set alpha value ) d) Make a Conclusion, ( as a sentence, in regard to students doing their homework equa use the CHISQ.DIST.RT function NOTE: "X" is your Sum from the equation above NOTE: Deg_freedom = n-1 p-value = c) Make a Decision ( compare your p-value with your pre-set alpha value ) d) Make a Conclusion, ( as a sentence, in regard to the variance of waiting times in a doc # 8, Extra-Credit ( up to + 2 points ) Data: number of pages cost of textbook # 3 Test of a Single Variance ( refer to section 11.6 and as similar to practice problems # 6 a) Using the test of a single variance equation, b) From your chi-square X 2 statistic value, now find your p-value:

280 $118.49 100 $63.15 225 $212.50 123 $47.83 550 $190.24 462 $185.24 675 $228.69 845 $275.25 524 $194.23 430 $75.32 715 $213.89 803 $263.24 684 $218.25 758 $275.36 112 $22.71 475 $175.29 x y ( new y ) ( new y ) number of pages cost of textbook x 2 Std dev x 2 std dev ( - ? ) ( + ? ) 140 $85.87 256 $123.55 G) Graphical Process for Identifying\Removing 3 Outliers

45 $8.52 613 $275.75 350 $112.25 194 $43.45 75 $45.21 585 $178.69 158 $35.68 600 $201.25 209 $65.75 450 $132.89 500 $145.87 731 $242.58 315 $99.99 824 $236.34 710 $257.54 365 $135.33 167 $41.75 430 $177.56 268 $135.20 585 $215.36 378 $175.68 647 $225.89 341 $150.00 430 $190.23 175 $55.49 243 $88.69 648 $185.24 186 $85.99 235 $87.68 753 $254.21 450 $167.99 386 $155.62 280 $118.49 100 $63.15 225 $212.50 123 $47.83

450 $132.89 500 $145.87 731 $242.58 315 $99.99 824 $236.34 710 $257.54 365 $135.33 167 $41.75 430 $177.56 268 $135.20 585 $215.36 378 $175.68 647 $225.89 341 $150.00 430 $190.23 175 $55.49 243 $88.69 648 $185.24 186 $85.99 235 $87.68 753 $254.21 450 $167.99 386 $155.62 280 $118.49 100 $63.15 225 $212.50 123 $47.83 550 $190.24 462 $185.24 675 $228.69 845 $275.25 524 $194.23 430 $75.32 715 $213.89 803 $263.24

684 $218.25 758 $275.36 112 $22.71 475 $175.29 x y number of pages cost of textbook H) Recalculating a new regression line after 3 removing outliers, n = 47

h 50 % or 10 points if completed work ) and the original Assignment # 9 Fo tax text on page 627 ) ribution a uniform distibution. Note- fill these columns and then sum 289 19.2667 121 8.066 64 4.266 36 2.4 9 0.6 1 0.0666 100 6.666 41.3313 df ( n -1 ) 6 ( O-E ) 2 (0-E) 2 /E Sum ( ∑ )

ally throughout the week). , X2 ctor's office). 65-68 on page 658 of the Open Stax text )

g) SUMMARY OUTPUT SUMMARY OUTPUT Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Intercept X Variable 1

Compare these values to the residuals in column four of th Calculate s = equals We are looking for all data points for which the residual is g √(/(50−2))

equals the SSE ( Sum of Squared Errors ) Please refer to pa use LINEST functi Slope ( b value ) Slope for x Standard error for x F statistic Regression sum of squares PEARSON, r equals R 2

Note: To use Excel's LINEST fuinction do the following steps: 1) Select the middle 10 cells in the middle of part c below ( N92:O96 ). 2) Go to the top menu bar for Formulas>More Functions>Statistical and scroll down to LINE 3) When the LINEST "pop-up" box appears, enter the y and x array ( column) data, then ent 4) Before you hit the "Ok" button or press enter, hold your CTRL + SHIFT+ ENTER key at the use LINEST function ( holding the Slope ( b value ) Intercept ( a Slope for x Standard error for x F statistic Regression sum of squares R 2 use the PEARSON function to obtain the correlation coefficient, r , = the coefficient of determination , r 2 , =