ANOVA - true/false - Numbas at mathcentre.ac.uk

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Mario Orsi

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Ready to use

5 years, 2 months ago

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Mario Orsi 4 years, 2 months ago

Published this.

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Mario Orsi 5 years, 2 months ago

Gave some feedback: Ready to use

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Mario Orsi 5 years, 2 months ago

Published this.

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Mario Orsi 5 years, 2 months ago

Created this as a copy of Paired data - true/false.

Name	Status	Author	Last Modified
Bonding - true/false	Ready to use	Mario Orsi	02/05/2023 19:37
Inference for proportions - true/false	Ready to use	Mario Orsi	15/05/2023 11:12
Chi-square: true/false	Ready to use	Mario Orsi	08/12/2021 10:54
Paired data - true/false	Ready to use	Mario Orsi	31/01/2020 13:19
ANOVA - true/false	Ready to use	Mario Orsi	29/09/2021 09:29
Linear regression - true/false	Ready to use	Mario Orsi	28/04/2021 15:45
Multiple regression - true/false	Ready to use	Mario Orsi	17/05/2023 10:18
Confidence intervals - true/false	Ready to use	Mario Orsi	27/03/2020 16:48

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Question statement

Identify each of the following statements as true or false in relation to the analysis of variance (ANOVA) method:

Give any introductory information the student needs.

			Name	Type	Generated Value

t_statements	list	List of 13 items
f_statements	list	List of 13 items
statements	list	List of 26 items
statement_marks	list	Nested 26×2 list
choices	list	[ 16, 5, 21, 0, 22, 11 ]

			Name	Type	Generated Value

k	integer	5
dfG	integer	4
n	integer	37
dfE	integer	32
alpha	integer	1
alphaStar	decimal	dec("0.100")
K_bonf	rational	10

Automatically regenerate variables?

Name

Data type

Value

(text strings)

Description

Describe what this variable represents, and list any assumptions made about its value.

Can an exam override the value of this variable?

Generated value: `list`

[ "Null hypothesis (H$_0$): The mean is the same across all groups.", "Alternative hypothesis (H$_A$): At least one mean is different.", "It is inappropriate to examine all data by eye (informal testing) and only afterwards decide which groups to formally test.", "For $\\var{k}$ groups and $\\var{n}$ total observations, $df_G=\\var{dfG}$.", "For $\\var{k}$ groups and $\\var{n}$ total observations, $df_E=\\var{dfE}$.", "The larger the variability between group means relative to the within-group variability, the stronger the evidence against the null hypothesis.", "For $\\var{k}$ groups and an original significance level $\\alpha=\\var{alpha}\\%$, testing all possible pairs requires a modified significance level $\\alpha^*=\\var{alphaStar}\\%$.", "All else being equal, larger differences in means between groups increase the evidence favouring the alternative hypothesis.", "All else being equal, larger within-group variations decrease the evidence favouring the alternative hypothesis.", "Rejecting the null hypothesis indicates evidence that at least one group mean is different from one another.", "If the null hypothesis is true, any variation in the sample means is due to chance.", "Rejecting the null hypothesis does not imply that a significant difference in the pairwise comparisons can be found.", "As the number of groups increases, the modified significance level for pairwise tests decreases." ]

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