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- Final Exam
- Problem 1
- Problem 2
- Problem 3
- Problem 4
- I'm having trouble recoding the variables, such as drug and wild, so that I can perform the necessary tests to make comparisons between mouse genotype and drug treatment. How do I rename these variables that I can do the statistical tests of comparison?
- part 1:Is this question most appropriately handled similarly to the serial data analysis on the last day of class, where every mouse gets boiled down to one number, and xy plots done in lattice? Alternatively can this be done in Rcmdr?
- Part 1: Should we omit extreme or outlying variables from our descriptive analysis, table, and figure? The way the question is phrased, "subsequent analysis", it seems as if all data should be included in the initial part of the question. Is this correct?
- Part3: Because there are more subjects in the Drug A group compared to the Drug B group, R limits the types of statistical tests I can perform. Is there a way to get around this?
- Part4: This question about significant change doesn't specify if we are separating drugA and drugB. I can report the results of two tests, asking whether there is a significant change for drugA or for drugB. Or I can report one test, asking if the change for drugA is significantly different from the change in drugB.

- Problem 5
- Part 1: I have no idea what you want here. The assumptions depend on the analysis I design in part 2. If my analysis is non-parametric, then normality is a non-issue (for instance). What sort of assumptions are independent of my analytical method?
- Number 1: In order to "design a graphic", don't we need data? Or, are we to assume that we can make up our own data for this question

- Homework 4
- Problem 1
- To find the probabiliity of an event, don't you divide the occurrence of that event by the total tries, as in getting 3 when rolling dice? For example, it you roll the dice 12 times, and you get 3 two times, the probability of rolling 3 is 1/6 right?
- So in problem 1, the number of times one picked a certain kind of flower was given out the total number of flowers. Wouldn't you then say the probability of being a particular color and height is the number of flowers of that color and height out of the total number of flowers?
- Why does multiplying the individual probabilities of color and height not equal the observed number of flowers of that same color and height?
- When calculating a CI for the OR needed in Q1 part 3, how do I get "n"? Also how do I calculate standard deviation/ variance?
- I have spent considerable time on Q1 p4 and remain lost. It sounds like you are asking for a partial F test or something.

- Quiz 3 (Take Home)
- Midterm
- R Problems
- Problem 1
- Problem 2
- Problem 3
- Problem 4
- How do I find the exact confidence interval. I can't seem to find anything in my notes, or the class handout on this topic.
- Can you explain the difference between part 8 and part 9. I am having difficulty differentiating between exactly what is being asked in each question
- Is there an Equation that can be used to calculate sigma in question 10?

- Problem 5
- A clarification from class. You said that obtaining F by using the 'compare two models' function, one model adjusted and the other model full is not the way to go for obtaining partial F, but it was how you obtain partial SSR's for adjusted variables?
- #2 "Interpret the t statistic for the age x sex effect." What are you talking about here? I can give you a t-statistic for age or sex, or an F-statistic for the whole model
- How would I use t-tests to assess whether each of the lead levels is needed in predicting maxfwt once the other lead level is adjusted for. What is meant by "adjusted for"?
- How would I find the weighted combination of lead levels that best predicts maxfwt?
- Is distance from the smelting plant represented by the "area" variable in the lead dataset?
- Scatterplot error "Cannot coerce "labelled" into a data.frame" How do I fix the problem so I can view a scatterplot. Only occurs when trying to set the group as "sex".
- Does the sex variable need to be recoded?
- When making a linear model, how do you allow the slope of one variable to vary with another?
- For #4 what is meant by combining the two lead levels? Does this mean I need to define a new variable in R or group ld72 and ld73 in some way? To "add age and sex", does this mean defining a new linear model such as maxfwt ~ ld72*ld73*age*sex?

- HW #3
- HW #2
- Do non-parametric tests have degrees of freedom?
- Factor variables
- Importing the data
- Computing P-values
- Calculating test statistics "by hand"
- Can I get really large test statistics
- Is it required to present a summary table of all the variables in the sepsis data set (Homework 2)?
- Questions about reporting confidence intervals

- HW #1

- Definitely remove the extreme data points when doing the remaining parts of problem 4
- For part 1, definitely say which data points you removed in your paragraph describing the data
- You are right that the question is not clear as to whether or not the extreme values should be in the table and figure, so either is acceptable for full credit. I would recommend removing the extreme points from any plots and tables (like you would do for a paper) because that will be the most helpful when answering the other parts of the problem. You only need to turn in one figure & table, but looking at additional plots may be helpful.

`cannot coerce class "labelled" into a data.frame`

when analyzing or graphing the `lead`

dataset, you can either install and load the `Hmisc`

package, or use a version of the `lead`

dataset that does not have labels. It may be obtained here.
I keep having problems with R commander freezing when I am working with a dataset. Is there a way around this problem?
`age`

is modified by `sex`

(equivalent to whether the effect of `sex`

is modified by `age`

).
`maxfwt`

once the other lead level is adjusted for. What is meant by "adjusted for"? `R Problems`

above.
`sex`

variable need to be recoded? `factor`

variable and does not need to be recoded.
`age*(sex=='male')`

. In R's modeling formula you separate two variables by an asterisk instead of a plus to force the main effects and the (automatically created) products (interaction effects) to be included. For example, a model `y ~ height*weight`

would generate a model with an intercept, a slope for `height`

, a slope for `weight`

, and a slope for the product of the two.
`ld72`

and `ld73`

is needed.
x <- 1:5 y <- c(98,198,315,380,530) a <- ... b <- ... plot(x,y) abline(a,b)

yhat <- a + b*x yhat # prints the results y - yhat # prints residuals

`Rcmdr`

under Windows you can paste the entire URL into the file name box when using the `Import`

menu.
2*(1 - pt(1.96, 1000))

`Rcmdr`

menu to perform a statistical test, the P-value should be part of the output.
`.sav`

file and save the address (URL). Under `Rcmdr`

you can paste this URL into the file name field in the import dialog. Edit | Attach | Print version | History: r73 < r72 < r71 < r70 | Backlinks | View wiki text | Edit wiki text | More topic actions

Topic revision: r73 - 13 Apr 2013, FrankHarrell

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