Page 1 of 1

Golfer Ai Miyazato Alena Sharp Alison Lee Alison Walshe Amelia Lewis Amy Anderson Amy Yang Angela Stanford Anna Nordqvis

Posted: Fri May 06, 2022 6:01 am
by answerhappygod
Golfer Ai Miyazato Alena Sharp Alison Lee Alison Walshe Amelia Lewis Amy Anderson Amy Yang Angela Stanford Anna Nordqvis 1
Golfer Ai Miyazato Alena Sharp Alison Lee Alison Walshe Amelia Lewis Amy Anderson Amy Yang Angela Stanford Anna Nordqvis 1 (287.46 KiB) Viewed 75 times
Golfer Ai Miyazato Alena Sharp Alison Lee Alison Walshe Amelia Lewis Amy Anderson Amy Yang Angela Stanford Anna Nordqvist Ariya Jutanugarn Ashleigh Simon Austin Ernst Ayako Uehara Azahara Munoz Beatriz Recari Belen Mozo Brittany Lang Brittany Lincicome Brooke Pancake Candie Kung Carlota Ciganda Caroline Hedwall Caroline Masson Catriona Matthew Charley Hull Chella Choi Cheyenne Woods Christel Boeljon Christina Kim Cristie Kerr Danielle Kang Demi Runas Dewi Claire Schreefel Dori Carter Eun-Hee Ji Garrett Phillips Gerina Piller Giulia Sergas Ha Na Jang Haeji Kang Earnings ($) Scoring Ave. 57017 72.000 27127 72.800 136411 70.722 66038 72.450 16524 73.333 20459 73.400 470755 70.469 93913 71.464 254749 70.000 255656 70.538 2891 73.800 118270 71.154 24674 73.167 140995 70.125 108561 71.846 17927 73.727 93959 71.654 497758 70.571 17003 73.222 20641 72.722 191247 70.750 26939 72.900 100978 71.800 79920 71.700 50157 72.125 95580 71.857 20999 73.444 11462 74.500 79135 72.233 303597 71.038 105003 71.292 8064 73.571 14410 73.167 6681 74.750 49013 72.429 2579 75.500 85944 72.000 2855 75.143 227340 70.417 19486 73.682 Greens in Reg. 0.702 0.689 0.716 0.653 0.636 0.708 0.752 0.718 0.788 0.735 0.700 0.722 0.657 0.753 0.716 0.634 0.703 0.698 0.623 0.688 0.762 0.775 0.720 0.756 0.729 0.718 0.664 0.646 0.715 0.741 0.688 0.698 0.664 0.667 0.677 0.722 0.720 0.667 0.766 0.657 Putting Ave. Drive Accuracy 30.040 0.788 30.650 0.694 29.170 0.798 29.550 0.683 29.720 0.701 31.600 0.729 30.030 0.739 29.960 0.763 29.820 0.776 29.190 0.647 30.900 0.829 30.080 0.723 30.330 0.813 29.380 0.772 30.380 0.731 30.230 0.668 29.850 0.687 29.070 0.658 29.390 0.773 30.220 0.679 30.390 0.727 32.450 0.668 30.470 0.678 31.250 0.775 31.630 0.672 30.540 0.861 30.560 0.781 31.380 0.785 30.400 0.755 30.040 0.747 29.000 0.750 31.640 0.758 30.560 0.709 31.060 0.624 29.930 0.838 33.670 0.670 30.570 0.701 31.930 0.707 30.170 0.797 30.270 0.718
Haru Nomura Hee Kyung Seo Hee Young Park Hyo Joo Kim I.K. Kim Ilhee Lee Inbee Park Jane Park Jaye Marie Green Jennifer Johnson Jennifer Rosales Jennifer Song Jenny Shin Jessica Korda Ji Young Oh Jing Yan Joanna Klatten Jodi Ewart Shadoff Ju Young Park Juli Inkster Julieta Granada Karin Sjodin Karine Icher Karlin Beck Karrie Webb Katherine Kirk Katie Burnett Kelly Shon Kelly Tan Kendall Dye Kim Kaufman Kris Tamulis Kristy McPherson Laetitia Beck Lee-Anne Pace Lexi Thompson Line Vedel Lisa Ferrero Lizette Salas Lydia Ko Mallory Blackwelder 47385 2511 48998 347014 30892 240022 426326 45208 35292 26828 3764 39199 157418 198649 5876 3230 17217 30627 3155 13064 82519 5461 110919 5790 94384 35056 39333 24228 13890 2852 45294 23824 11359 13736 46418 175510 24787 9253 65576 608810 2366 71.889 74.600 72.000 69.300 72.438 70.813 69.625 73.227 73.625 72.500 73.667 72.400 71.100 70.800 72.929 73.250 73.571 72.667 74.833 72.917 71.964 74.167 71.563 75.750 71.571 73.591 72.450 73.000 73.929 75.000 72.364 73.227 74.000 73.125 73.167 70.542 73.000 72.750 71.591 69.536 75.750 0.710 0.644 0.676 0.744 0.726 0.705 0.813 0.682 0.701 0.661 0.685 0.681 0.707 0.783 0.651 0.569 0.702 0.720 0.741 0.676 0.675 0.727 0.753 0.646 0.706 0.634 0.703 0.663 0.639 0.611 0.705 0.707 0.670 0.694 0.648 0.771 0.670 0.722 0.687 0.815 0.634 30.720 31.800 29.540 28.800 30.750 29.130 30.170 30.950 31.060 30.200 31.580 29.600 29.500 30.770 30.000 28.880 31.640 31.130 33.330 30.580 29.290 32.080 30.660 32.880 30.070 30.050 30.400 30.500 30.860 31.080 30.680 31.180 31.190 31.630 30.280 30.420 30.120 30.920 29.360 29.960 31.920 0.756 0.771 0.774 0.796 0.765 0.763 0.783 0.803 0.690 0.780 0.841 0.773 0.807 0.733 0.888 0.786 0.652 0.732 0.773 0.756 0.864 0.712 0.825 0.767 0.793 0.788 0.739 0.813 0.835 0.814 0.742 0.753 0.846 0.690 0.760 0.702 0.820 0.702 0.795 0.783 0.814
Mallory Blackwelder Maria Hernandez Mariajo Uribe Marina Alex Marissa Steen Meena Lee Mi Hyang Lee Mi Jung Hur Michelle Wie Mika Miyazato Min Lee Min Seo Kwak Mina Harigae Minjee Lee Mirim Lee Mo Martin Morgan Pressel Moriya Jutanugarn Na Yeon Choi Natalie Gulbis Nicole Castrale P.K. Kongkraphan Paula Creamer Paula Reto Paz Echeverria Pernilla Lindberg Perrine Delacour Pornanong Phatlum Q Baek Ryann O'Toole Sakura Yokomine Sandra Gal Sarah Jane Smith Sarah Kemp Se Ri Pak Sei Young Kim Seon Hwa Lee Shanshan Feng Simin Feng So Yeon Ryu SooBin Kim 2366 37346 57179 26087 9072 34578 166728 17373 50427 64020 22288 8710 69839 64545 335001 90813 212545 126169 314599 7382 3764 3738 75673 29058 30477 77117 17092 129325 62229 5796 51888 129005 10550 9294 36083 429735 5461 178981 6949 148816 7953 75.750 72.667 72.406 73.136 73.714 72.500 71.929 73.682 71.962 71.615 73.000 73.857 72.067 72.182 70.786 71.933 71.615 71.038 71.500 72.000 73.400 74.000 71.607 73.400 74.500 72.133 74.333 71.269 72.538 73.643 72.357 71.036 73.313 73.917 73.071 70.154 73.273 70.700 73.286 71.208 73.600 0.634 0.694 0.694 0.694 0.643 0.669 0.768 0.588 0.679 0.647 0.698 0.667 0.706 0.702 0.764 0.754 0.643 0.769 0.726 0.700 0.661 0.577 0.710 0.674 0.705 0.704 0.625 0.720 0.686 0.651 0.706 0.710 0.663 0.602 0.659 0.763 0.616 0.772 0.683 0.755 0.689 31.920 30.500 30.470 30.910 30.070 30.040 31.790 28.590 29.920 28.580 31.000 30.790 30.100 30.270 30.360 30.900 28.500 30.650 30.250 29.800 30.500 30.330 29.930 31.070 32.190 30.330 30.750 30.120 29.920 30.360 30.570 29.500 30.630 29.420 30.640 30.120 29.270 30.850 30.860 31.000 31.600 0.814 0.797 0.715 0.798 0.803 0.810 0.785 0.588 0.602 0.859 0.793 0.810 0.800 0.772 0.681 0.917 0.687 0.811 0.760 0.836 0.736 0.619 0.819 0.717 0.741 0.708 0.724 0.830 0.704 0.758 0.778 0.804 0.712 0.721 0.638 0.736 0.827 0.803 0.662 0.800 0.836
Sophia Popov Stacy Lewis Sun Young Yoo Suzann Pettersen Sydnee Michaels Therese Koelbaek Thidapa Suwannapura Tiffany Joh Victoria Elizabeth Wei Ling Hsu Xiyu Lin Yani Tseng Yueer Cindy Feng 2891 648730 157068 129145 42693 7887 18952 20436 3293 30797 33135 125597 29718 73.625 69.321 70.778 71.000 72.500 73.400 73.083 73.278 74.000 73.091 71.200 73.167 71.667 0.618 0.748 0.713 0.742 0.728 0.633 0.660 0.759 0.733 0.674 0.752 0.657 0.676 28.500 28.430 29.280 30.350 30.900 29.800 30.290 31.940 33.000 30.450 30.400 30.280 29.830 0.649 0.791 0.754 0.793 0.750 0.732 0.831 0.836 0.686 0.808 0.757 0.602 0.702
DATAfile: 2014LPGAStats3 A statistical program recommended. You may need to use the appropriate technology to answer this question. The Ladies Professional Golfers Association (LPGA) maintains statistics on performance and eamings for members of the LPGA Tour. Year-end performance statistics for 134 golfers for 2014 appear in the file named 2014LPGAStats3.+ Earnings ($1,000s) is the total earnings in thousands of dollars; Scoring Avg. is the average score for all events; Greens in Reg. is the percentage of time a player is able to hit the greens in regulation; Putting Avg. is the average number of putts taken on greens hit in regulation; and Drive Accuracy is the percentage of times a tee shot comes to rest in the fairway. A green is considered hit in regulation if any part of the ball is touching the putting surface and the difference between the value of par for the hole and the number of strokes taken to hit the green is at least 2. greens hit in regulation. Use x, for Putting Avg. (Round your numerical (a) Develop an estimated regression equation that can be used to predict the average score for all events given the average number of putts taken values to two decimal places.) (b) Develop an estimated regression equation that can be used to predict the average score for all events given the percentage of time a player is able to hit the greens in regulation, the average number of putts taken on greens hit in regulation, and the percentage of times a player's tee shot comes to rest in the fairway. Use x₂ for Greens in Reg. and x3 for Drive Accuracy. (Round your numerical values to two decimal places.) (c) At the 0.05 level of significance, test whether the two independent variables added in part (b), percentage of time a player is able to hit the greens in regulation and the percentage of times a player's tee shot comes to rest in the fairway, contribute significantly to the estimated regression equation developed in part (a). State the null and alternative hypotheses. No: B₁0 H₂! B₁ #0 Ho: B₁ 0 H₂: P₁ = 0 Ho: B₂-03-0 H₂: One more of the parameters is not equal to zero. OH: One or more of the parameters is not equal to zero. Hai P₂-03-0
Find the value of the test statistic. (Round your answer to two decimal places.) Find the p-value. (Round your answer to three decimal places.) p-value = Is the addition of the variables x₂ and x3 significant? Do not reject Ho. We conclude that the addition of the variables. X₂ and X3 X2 and x3 is not significant. Reject Ho. We conclude that the addition of the variables ● Reject Ho. We conclude that the addition of the variables x₂ and x3 is significant. Do not reject Ho. We conclude that the addition of the variables x₂ and x3 is not significant. is significant.