Identify the correct function call in base R to perform one-way ANOVA where y is

Question

Identify the correct function call in base R to perform one-way ANOVA where y is the numeric response variable and x is the grouping variable. _______ a. lm (anova(x ~ y)) b. lm (anova(y ~ x) c. anova (lm(y ~ x)) d. anova (lm(x ~ y) e. anova (lm(y ~ x)) f. plotmeans (y ~ x) g. describeBy (y, x) h. none of the above A one-way data set was analyzed by Anova. The p-value was 0.0015, explained R-square was 1.3% and Cohen's D was 0.09. Was total N of this data set (i.e., the number of rows in the data frame) likely to have been, low N or high N? leftarrow circle your answer A data set was analyzed by one-way ANOVA. To the dismay of the scientist the F-statistic lacked statistical significance. In R, the observed data resided in the data frame: my.frame which had 22 rows by 2 columns. The investigator was curious about what the ANOVA would be if more data had been collected but she did not know how to perform formal, statistical power analysis. As a crude indication of what might happen if more data had been collected, she doubled the observed data s by simply adding a copy of it below the original data frame, such that now a new data frame: big.frame had 44 rows with the same number of columns. In R this is easily accomplished by > big.frame

Explanation / Answer

Question 1. Option is none of above beacuse for one- way anova correct function is aov(y ~ x) or anova(y~x).

Question 2. low N as the total variation is explained by model is low.

Question 3. cause F statistics statistically more siginficant

Question 4.   In statistical hypothesis testing, a type I error (or error of the first kind) is the incorrect rejection of a true null hypothesis (a "false positive"). Usually a type I error leads one to conclude that a supposed effect or relationship exists when in fact it doesn't. Examples of type I errors include i) a test that shows a patient to have a disease when in fact the patient does not have the disease, ii )a fire alarm going on indicating a fire when in fact there is no fire, or iii )an experiment indicating that a medical treatment should cure a disease when in fact it does not.

Question 5.

The null hypothesis for ANOVA is that the mean (average value of the dependent variable) is the same for all groups. The alternative or research hypothesis is that the average is not the same for all groups.

i.e

where k = the number of independent comparison groups.

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