// Numbas version: finer_feedback_settings {"name": "Jinhua's copy of Two-way ANOVA Practice", "duration": 0, "metadata": {"notes": "", "description": "
Statistics and probability. Two way-anova question.
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\n$T_1=\\var{cols[0]},\\;T_2=\\var{cols[1]},\\;T_3=\\var{cols[2]},\\;T_4=\\var{cols[3]}$
\nSubject totals are:
\n$B_1=\\var{t[0]},\\;B_2=\\var{t[1]},\\;B_3=\\var{t[2]},\\;B_4=\\var{t[3]},\\;B_5=\\var{t[4]}$
\n$\\sum \\sum x^2 = \\var{ssq}$ and $G= \\var{tot}$
\nNow using the above find the following, all to 2 decimal places:
\n$\\displaystyle TSS\\;=\\;$[[0]], $\\displaystyle BTSS\\;=\\;$[[1]]
\n$\\displaystyle BBSS \\;=\\;$[[2]], $\\displaystyle RSS\\;=\\;$[[3]]
\n(Find $RSS$ using the values to 2 decimal places for $TSS,\\;BTSS,\\;BBSS$.)
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\n\n
Source | df | SS | MS | VR |
---|---|---|---|---|
Between Treatments | \n[[0]] | \n[[1]] | \n[[2]] | \n[[3]] | \n
Between Blocks | \n[[4]] | \n[[5]] | \n[[6]] | \n[[7]] | \n
Residual | \n[[8]] | \n[[9]] | \n[[10]] | \n- | \n
Total | \n[[11]] | \n[[12]] | \n- | \n- | \n
Input all numbers to 2 decimal places.
\nNote that VR is found by taking the ratio of two of the values in this table.
", "showCorrectAnswer": true, "marks": 0}, {"displayType": "radiogroup", "choices": ["$p$ less than $0.1\\%$
", "$p$ lies between $0.1\\%$ and $1\\%$
", "$p$ lies between $1 \\%$ and $5\\%$
", "$p$ lies between $5 \\%$ and $10\\%$
", "$p$ is greater than $10\\%$
"], "displayColumns": 1, "prompt": "Give the value of $VR$ you have found, choose the range for the $p$ value by looking up the critical values of $F_{3,12}$ (one-sided).
\n$10\\%$ | \n$5\\%$ | \n$1\\%$ | \n$0.1\\%$ | \n
$2.61$ | \n$3.49$ | \n$5.95$ | \n$10.8$ | \n
Very Strong Evidence
", "Strong Evidence
", "Evidence
", "Weak Evidence
", "No Evidence
"], "displayColumns": 0, "prompt": "Given the $p$-value and the range you have found, what is the strength of evidence against the null hypothesis that there is no difference in the treatments offered by the sun-creams?
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", "distractors": ["", "", "", "", ""], "shuffleChoices": false, "scripts": {}, "minMarks": 0, "type": "1_n_2", "maxMarks": 0, "showCorrectAnswer": true, "matrix": "v", "marks": 0}, {"scripts": {}, "gaps": [{"correctAnswerFraction": false, "showPrecisionHint": false, "allowFractions": false, "scripts": {}, "type": "numberentry", "showCorrectAnswer": true, "minValue": "mean(r1[0])-tol", "maxValue": "mean(r1[0])+tol", "marks": 0.5}, {"correctAnswerFraction": false, "showPrecisionHint": false, "allowFractions": false, "scripts": {}, "type": "numberentry", "showCorrectAnswer": true, "minValue": "mean(r1[1])-tol", "maxValue": "mean(r1[1])+tol", "marks": 0.5}, {"correctAnswerFraction": false, "showPrecisionHint": false, "allowFractions": false, "scripts": {}, "type": "numberentry", "showCorrectAnswer": true, "minValue": "mean(r1[2])-tol", "maxValue": "mean(r1[2])+tol", "marks": 0.5}, {"correctAnswerFraction": false, "showPrecisionHint": false, "allowFractions": false, "scripts": {}, "type": "numberentry", "showCorrectAnswer": true, "minValue": "mean(r1[3])-tol", "maxValue": "mean(r1[3])+tol", "marks": 0.5}, {"correctAnswerFraction": false, "showPrecisionHint": false, "allowFractions": false, "scripts": {}, "type": "numberentry", "showCorrectAnswer": true, "minValue": "stderror-tol", "maxValue": "stderror+tol", "marks": 1}], "type": "gapfill", "prompt": "Enter the sample means for the sun-creams:
\nW: [[0]], X:[[1]], Y:[[2]], Z:[[3]]
\nAlso enter an estimate of the standard error of the mean: [[4]]
\n(Use the value to 2 decimal places you obtained above for $RMS$ to calculate the standard error of the mean).
", "showCorrectAnswer": true, "marks": 0}], "statement": "To test the effectiveness of sun-tan creams, five volunteers A, B, C, D, E each tried four creams W, X, Y, Z on various parts of their legs. They were then subjected to ultra-violet radiation and an estimate of the degree of burning was made (higher figures indicate greater burning). The results are given below with some totals:
\n\n | W | \nX | \nY | \nZ | \nTotals | \n
A | \n{r[0][0]} | \n{r[0][1]} | \n{r[0][2]} | \n{r[0][3]} | \n{t[0]} | \n
B | \n{r[1][0]} | \n{r[1][1]} | \n{r[1][2]} | \n{r[1][3]} | \n{t[1]} | \n
C | \n{r[2][0]} | \n{r[2][1]} | \n{r[2][2]} | \n{r[2][3]} | \n{t[2]} | \n
D | \n{r[3][0]} | \n{r[3][1]} | \n{r[3][2]} | \n{r[3][3]} | \n{t[3]} | \n
E | \n{r[4][0]} | \n{r[4][1]} | \n{r[4][2]} | \n{r[4][3]} | \n{t[4]} | \n
Totals | \n{cols[0]} | \n{cols[1]} | \n{cols[2]} | \n{cols[3]} | \n{tot} | \n
You are given that $\\sum \\sum x^2=\\var{ssq}$ is the uncorrected sum of squares of the observations and you are asked to:
\n\n
Two-way ANOVA example, 5 subjects, 4 treatments.
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