Answer to Question #94859 in Statistics and Probability for Octavius
Predict week 11 using the different methods requested and then use historical analysis to determine the best method.
Smoothing:
Week Attendance
1 350
2 500
3 750
4 705
5 820
6 743
7 880
8 900
9 795
10 900 three week four week three week weighted
Next Week Projection (week 11):
Longest Regression:
1) Use regression analysis to predict week 11 in the above example:
Regression can also be used for predictions within the relevant range:
1
2019-09-23T07:05:11-0400
"\\def\\arraystretch{1.5}\n \\begin{array}{c:c}\n Week & Attendance \\\\ \\hline\n 1 & 350 \\\\\n \\hdashline\n2 & 500 \\\\\n \\hdashline\n3 & 750 \\\\\n \\hdashline\n4 & 705 \\\\\n \\hdashline\n5 & 820 \\\\\n \\hdashline\n6 & 743 \\\\\n \\hdashline\n7 & 880 \\\\\n \\hdashline\n8 & 900 \\\\\n \\hdashline\n 9 & 795\\\\\n \\hdashline\n10 & 900 \\\\\n \\hline\n\\end{array}"
"\\sum x_i=55, \\sum y_i=7343"
"\\sum x_i^2=385, \\sum y_i^2=5682899"
"\\sum x_iy_i=44493"
"mean:\\ \\bar{x}={\\sum x_i \\over n},\\ \\bar{y}={\\sum y_i \\over n}""mean:\\ \\bar{x}={55\\over 10}=5.5,\\ \\bar{y}={7343 \\over 10}=734.3""Trend \\ line: y=A+Bx, B={S_{xy} \\over S_{xx}}, A=\\bar{y}-B\\bar{x}""correlation\\ coefficient: r={S_{xy}\\over \\sqrt{S_{xx}}\\sqrt{S_{yy}}}"
"S_{xx}=\\sum(x_i-\\bar{x})^2=\\sum x_i^2-n\\cdot\\bar{x}^2"
"S_{xx}=385-10\\cdot5.5^2=82.5"
"S_{yy}=\\sum(y_i-\\bar{y})^2=\\sum y_i^2-n\\cdot\\bar{y}^2"
"S_{yy}=5682899-10\\cdot734.3^2=290934.1"
"S_{xy}=\\sum(x_i-\\bar{x})(y_i-\\bar{y})=\\sum x_iy_i-n\\cdot\\bar{x}\\bar{y}"
"S_{xy}=44493-10\\cdot5.5\\cdot734.3=4106.5"
"B={S_{xy} \\over S_{xx}}={4106.5\\over 82.5}\\approx49.77575758"
"A=\\bar{y}-B\\bar{x}=734.3-49.77575758\\cdot5.5=460.5333333"
"r={S_{xy}\\over \\sqrt{S_{xx}}\\sqrt{S_{yy}}}={4106.5\\over \\sqrt{82.5}\\sqrt{290934.1}}\\approx0.8382"
"y=460.5333333+49.77575758x"
"y(11)=460.5333333+49.77575758(11)\\approx1008"
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