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### Question 2: 

For each of the following regressions, explain what is wrong with the output of `lm( )`,

and why exactly it occurred. Explain your answers with appropriate plots or tables where possible.


```{r, eval = TRUE}

# a

#lm_a = lm(Price ~ Subwoofer, data = laptops)


# b

lm_b = lm(Price ~ Max.Horizontal.Resolution^2, data = laptops)

summary(lm_b)


# c

lm_c = lm(Price ~ Manufacturer + Operating.System, data = laptops)


# d

lm_d1 = lm(Price ~ Processor.Speed+Processor, data = laptops)

lm_d2 = lm(Price ~ Processor.Speed*Processor, data = laptops)


```


```


```


***


## ANOVA for nested models


Recall that we can use ANOVA tests to compare two multiple regressions, when one model is nested in the other. This is particularly useful when the models have many factors, so it might be hard to tell which variable is more significant from the t-scores.


***

### Question 3:

Consider the following model:

```{r, eval = FALSE}

 lm_3 = lm(Price ~ Port.Replicator + Bluetooth + Manufacturer, data = laptops)

```

If you had to remove exactly one of the three variables from the model, which one would you remove? Why?


```{r, eval = FALSE}

YOUR CODE HERE

```


```

```


This is R assignment. Please provide explanations and put the answer in YOUR CODE HERE. Thank you.

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