// Numbas version: finer_feedback_settings {"name": "Perform t-test for hypothesis given sample mean and standard deviation", "extensions": ["stats"], "custom_part_types": [], "resources": [], "navigation": {"allowregen": true, "showfrontpage": false, "preventleave": false, "typeendtoleave": false}, "question_groups": [{"pickingStrategy": "all-ordered", "questions": [{"variable_groups": [], "variables": {"tol": {"templateType": "anything", "group": "Ungrouped variables", "definition": "0.001", "description": "", "name": "tol"}, "dmm": {"templateType": "anything", "group": "Ungrouped variables", "definition": "if(pval<2,[1,0],[0,1])", "description": "", "name": "dmm"}, "thisamount": {"templateType": "anything", "group": "Ungrouped variables", "definition": "random(70..90)", "description": "", "name": "thisamount"}, "confl": {"templateType": "anything", "group": "Ungrouped variables", "definition": "random(90,95,99)", "description": "", "name": "confl"}, "pval": {"templateType": 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Step 1: Null Hypothesis

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$\\operatorname{H}_0\\;: \\; \\mu=\\;$[[0]]

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Step 2: Alternative Hypothesis

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$\\operatorname{H}_1\\;: \\; \\mu \\neq\\;$[[1]]

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Step 3: Test statistic

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Should we use the z or t test statistic? [[0]] (enter z or t).

\n

Now calculate the test statistic = ? [[1]] (to 3 decimal places)

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Step 4: p-value

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Use tables to find a range for your $p$-value. 

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Choose the correct range here for $p$ : [[0]]

\n ", "showCorrectAnswer": true, "marks": 0}, {"scripts": {}, "gaps": [{"displayType": "radiogroup", "choices": ["{evi[0]}", "{evi[1]}", "{evi[2]}", "{evi[3]}"], "displayColumns": 0, "distractors": ["", "", "", ""], "shuffleChoices": false, "scripts": {}, "minMarks": 0, "type": "1_n_2", "maxMarks": 0, "showCorrectAnswer": true, "matrix": "mm", "marks": 0}, {"displayType": "radiogroup", "choices": ["Retain", "Reject"], "displayColumns": 0, "distractors": ["", ""], "shuffleChoices": false, "scripts": {}, "minMarks": 0, "type": "1_n_2", "maxMarks": 0, "showCorrectAnswer": true, "matrix": "dmm", "marks": 0}, {"displayType": "radiogroup", "choices": ["{Correctc}", "{Fac}"], "displayColumns": 0, "distractors": ["", ""], "shuffleChoices": true, "scripts": {}, "minMarks": 0, "type": "1_n_2", "maxMarks": 0, "showCorrectAnswer": true, "matrix": [1, 0], "marks": 0}], "type": "gapfill", "prompt": "\n

Step 5: Conclusion

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Given the $p$ - value and the range you have found, what is the strength of evidence against the null hypothesis?

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[[0]]

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Your Decision:

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[[1]]

\n

 

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Conclusion:

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[[2]]

\n ", "showCorrectAnswer": true, "marks": 0}], "statement": "\n

{this} 

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{claim}

\n

{test}

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A sample of {n} {things}

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{resultis} £{m} with a standard  deviation of £{stand}.

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Perform an appropriate hypothesis test to see if the claim made by the online flight company is substantiated (use a two-tailed test).

\n ", "tags": ["checked2015", "MAS1403"], "rulesets": {}, "preamble": {"css": "", "js": ""}, "type": "question", "metadata": {"notes": "\n \t\t

2/01/2012:

\n \t\t

Added tag sc as has string variables in order to generate other scenarios.

\n \t\t

The jstat function studenttinv(critvalue,n-1) gives the critical p values correctly.

\n \t\t

Added tag diagram as the i-assess question advice has a nice graphic of the p-value and the appropriate decision.

\n \t\t", "licence": "Creative Commons Attribution 4.0 International", "description": "

Provided with information on a sample with sample mean and standard deviation, but no information on the population variance, use the t test to either accept or reject a given null hypothesis.

"}, "variablesTest": {"condition": "", "maxRuns": 100}, "advice": "\n

a)

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Step 1: Null Hypothesis

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$\\operatorname{H}_0\\;: \\; \\mu=\\;\\var{thisamount}$

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Step 2: Alternative Hypothesis

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$\\operatorname{H}_1\\;: \\; \\mu \\neq\\;\\var{thisamount}$

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b)

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We should use the t statistic as the population variance is unknown.

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The test statistic:

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\\[t =\\frac{ |\\var{m} -\\var{thisamount}|} {\\sqrt{\\frac{\\var{stand} ^ 2 }{\\var{n}}}} = \\var{tval}\\]

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to 3 decimal places.

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c)

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As  $n=\\var{n}$ we use the $t_{\\var{n-1}}$ tables.  We have the following data from the tables:

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{table([['Critical Value',crit[0],crit[1],crit[2]]],['p value','10%','5%','1%'])}

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We see that the $p$ value {pm[pval]}.

\n


d)

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Hence there is {evi1[pval]} evidence against $\\operatorname{H}_0$ and so we {dothis} $\\operatorname{H}_0$.

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{Correctc}

\n ", "contributors": [{"name": "Newcastle University Mathematics and Statistics", "profile_url": "https://numbas.mathcentre.ac.uk/accounts/profile/697/"}]}]}], "contributors": [{"name": "Newcastle University Mathematics and Statistics", "profile_url": "https://numbas.mathcentre.ac.uk/accounts/profile/697/"}]}