// Numbas version: finer_feedback_settings {"name": "Catherine's copy of Pearson1", "extensions": ["stats"], "custom_part_types": [], "resources": [], "navigation": {"allowregen": true, "showfrontpage": false, "preventleave": false, "typeendtoleave": false}, "question_groups": [{"pickingStrategy": "all-ordered", "questions": [{"tags": [], "preamble": {"css": "", "js": ""}, "variables": {"ss": {"definition": "[ssq[0]-t[0]^2/n,ssq[1]-t[1]^2/n]", "templateType": "anything", "description": "", "name": "ss", "group": "Ungrouped variables"}, "n": {"definition": "8", "templateType": "anything", "description": "", "name": "n", "group": "Ungrouped variables"}, "r2": {"definition": "tesarr(r1,darr(n,m,[random(1..m)]),9,m)", "templateType": "anything", "description": "", "name": "r2", "group": "Ungrouped variables"}, "corrcoef": {"definition": "precround(spxy/sqrt(ss[0]*ss[1]),3)", "templateType": "anything", "description": "", "name": "corrcoef", "group": "Ungrouped variables"}, "obj": {"definition": "['A','B','C','D','E','F','G','H']", "templateType": "anything", "description": "", "name": "obj", "group": "Ungrouped variables"}, "ssd": {"definition": "sum(map(x^2,x,d))", "templateType": "anything", "description": "", "name": "ssd", "group": "Ungrouped variables"}, "m": {"definition": "20", "templateType": "anything", "description": "", "name": "m", "group": "Ungrouped variables"}, "spcoef": {"definition": "precround(6*ssd/(n*(n^2-1)),3)", "templateType": "anything", "description": "", "name": "spcoef", "group": "Ungrouped variables"}, "rr2": {"definition": "rk(r2)", "templateType": "anything", "description": "", "name": "rr2", "group": "Ungrouped variables"}, "rr1": {"definition": "rk(r1)", "templateType": "anything", "description": "", "name": "rr1", "group": "Ungrouped variables"}, "vs": {"definition": "switch(spcoef >=0.952,[1,0,0,0,0],spcoef>=0.881,[0,1,0,0,0],spcoef>=0.738,[0,0,1,0,0],spcoef>=0.643,[0,0,0,1,0],[0,0,0,0,1])", "templateType": "anything", "description": "", "name": "vs", "group": "Ungrouped variables"}, "t": {"definition": "[sum(r1),sum(r2)]", "templateType": "anything", "description": "", "name": "t", "group": "Ungrouped variables"}, "v": {"definition": "switch(corrcoef >=0.905,[1,0,0,0,0],corrcoef>=0.834,[0,1,0,0,0],corrcoef>=0.707,[0,0,1,0,0],corrcoef>=0.621,[0,0,0,1,0],[0,0,0,0,1])", "templateType": "anything", "description": "", "name": "v", "group": "Ungrouped variables"}, "tsqovern": {"definition": "[t[0]^2/n,t[1]^2/n]", "templateType": "anything", "description": "", "name": "tsqovern", "group": "Ungrouped variables"}, "d": {"definition": "list(vector(rr1)-vector(rr2))", "templateType": "anything", "description": "", "name": "d", "group": "Ungrouped variables"}, "sxy": {"definition": "sum(map(r1[x]*r2[x],x,0..n-1))", "templateType": "anything", "description": "", "name": "sxy", "group": "Ungrouped variables"}, "spxy": {"definition": "sxy-t[0]*t[1]/n", "templateType": "anything", "description": "", "name": "spxy", "group": "Ungrouped variables"}, "k": {"definition": "3", "templateType": "anything", "description": "", "name": "k", "group": "Ungrouped variables"}, "r1": {"definition": "darr(n,m,[random(1..20)])", "templateType": "anything", "description": "", "name": "r1", "group": "Ungrouped variables"}, "ssq": {"definition": "[sum(map(x^2,x,r1)),sum(map(x^2,x,r2))]", "templateType": "anything", "description": "", "name": "ssq", "group": "Ungrouped variables"}, "tol": {"definition": "0.01", "templateType": "anything", "description": "", "name": "tol", "group": "Ungrouped variables"}}, "name": "Catherine's copy of Pearson1", "advice": "
The answers to all parts are given on revealing.
", "parts": [{"scripts": {}, "variableReplacements": [], "prompt": "\nExpenditure $(X)$ | \n$\\sum x=\\;$[[0]] | \n$\\sum x^2=\\;$[[1]] | \n
---|---|---|
Sales $(Y)$ | \n$\\sum y=\\;$[[2]] | \n$\\sum y^2=\\;$[[3]] | \n
Also find $\\sum xy=\\;$[[4]].
\nHence calculate the correlation coefficient $r$ correct to 3 decimal places:
\n$r=\\;$[[5]]
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The data presented in the table below shows the annual promotional expenditure (€000s) and corresponding sales figures (000s units) for eight small businesses.
\nBusiness | \n$\\var{obj[0]}$ | \n$\\var{obj[1]}$ | \n$\\var{obj[2]}$ | \n$\\var{obj[3]}$ | \n$\\var{obj[4]}$ | \n$\\var{obj[5]}$ | \n$\\var{obj[6]}$ | \n$\\var{obj[7]}$ | \n
---|---|---|---|---|---|---|---|---|
Expenditure $(X)$ | \n$\\var{r1[0]}$ | \n$\\var{r1[1]}$ | \n$\\var{r1[2]}$ | \n$\\var{r1[3]}$ | \n$\\var{r1[4]}$ | \n$\\var{r1[5]}$ | \n$\\var{r1[6]}$ | \n$\\var{r1[7]}$ | \n
Sales $(Y)$ | \n$\\var{r2[0]}$ | \n$\\var{r2[1]}$ | \n$\\var{r2[2]}$ | \n$\\var{r2[3]}$ | \n$\\var{r2[4]}$ | \n$\\var{r2[5]}$ | \n$\\var{r2[6]}$ | \n$\\var{r2[7]}$ | \n
\\[r=\\frac{n\\Sigma xy -\\Sigma x \\Sigma y}{\\sqrt{n\\Sigma x^2-(\\Sigma x)^2}\\sqrt{n\\Sigma y^2-(\\Sigma y)^2}}\\]
", "functions": {"tesarr": {"language": "jme", "definition": "if(marr(map(abs(x),x,list(vector(a)-vector(b))))Calculate the Pearson correlation coefficient on paired data and comment on the significance.
\nrebelmaths
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