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This is my exam preparation, which will be held completely in R. Teacher said that similar tasks will be there with very limited amount of time given for solving it. Here I need to recover linear regression values (i.e., where are a-i missing values) having only this R output. I don't have the input data so I can't just copy the command and reproduce the result.

Given coefficient is R output. I don't have the input data.

My question is how can I make it using R? Are there any specific commands? Or could it be done only manually? If it is possible only by manual calculation than please explain how to do it more effectively.

Please, describe it in detail.

Thank you so much for your help and deep explanation.

Ruslan Seletskiy
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  • Please add `[self-study]` tag and check https://stats.stackexchange.com/tags/self-study/info – Tim Dec 11 '15 at 21:09
  • Welcome to CV! Software questions are generally off-topic here—you may have more luck on StackOverflow. – Sean Easter Dec 11 '15 at 21:34
  • Here's a hint `t` = `Estimate`/`Std. Error` You're welcome – SASsy Dec 11 '15 at 21:10
  • @SeanEaster this is **not a software question** and it is **on-topic**, it asks about strictly statistics stuff. I do not understand the two votes for moving it to SO. What is the *programming* issue in this question that makes it suitable for SO? This is strictly about understanding regression, Wald test, F test etc. – Tim Dec 12 '15 at 22:19
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    @Tim "How can I make it using R" sounds exactly like a software question. If that question I quoted is not asking for R commands it needs to be reworded so it doesn't read like that's what it's asking for. – Glen_b Dec 13 '15 at 05:23
  • @Glen_b but the question is generally about interpreting R's output and if you can calculate the values by hand on if you need R for it... – Tim Dec 13 '15 at 08:26
  • @Tim I can't speak for the other voter, but I at least interpreted the question's focus as reproducing the example output. Though, having now reread the first paragraph, I take your point. I'd second Glen_b's comment on rewording. – Sean Easter Dec 14 '15 at 15:42

1 Answers1

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Since this seems to be a self-study question let me give you some hints. First, do you know what the columns in your output mean? Estimate is $\beta$ parameter, Std. Error is standard error and t value is $t$-value (or standardized parameter). Hypothesis tests are conducted using Wald test, i.e. $\beta/\mathrm{SE}(\beta)$. Knowing all this you can easily compute the values (a)-(g). As you can notice from column name Pr(>|t|) it is a probability from $t$-distribution, so knowing the previous values you can read the values from statistical tables for $t$-distribution or compute using appropriate R function. As about (i), you know the adjusted $R^2$, so you have just to revert the adjustment. By the way, it would be probably good idea to check in your handbook information about degrees of freedom in multiple regression and ANOVA (generally for the $F$ test) since this information may be helpful. See also this thread that also describes the lm output.

Tim
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    @RLearnsMath no need to thank. If you find some answer helpful in here you can upvote it (the upward arrow) or accept it (the "v" button) -- you can upvote multiple answers and accept only a single one. Unfortunately, you can upvote only after gaining some reputation. See https://stats.stackexchange.com/tour and welcome on our site! – Tim Dec 11 '15 at 21:24
  • Yes but how will I figure out the amount of observation in the data set? By manually computing each variable? – Ruslan Seletskiy Dec 11 '15 at 22:32
  • @RLearnsMath have a closer look at Tim's last sentence. – Stefan Dec 12 '15 at 02:15
  • Yes but I can do nothing with ANOVA just because I don't have sample size of the given data. – Ruslan Seletskiy Dec 12 '15 at 11:11
  • Knowing how degrees of freedom are calculated you can easily compute it from DF. – Tim Dec 12 '15 at 14:21
  • @RLearnsMath I edited and added two more links, I am sure they will help you to understand how to interpret degrees of freedom and how to use them. – Tim Dec 12 '15 at 22:15