Flashcards in Unit 4 : Hypothesis Testing & Confidence Intervals in Simple Linear Regression Deck (11)

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1

## When can we say that heteroscedasticity exists?

### When the variance of the error terms are not constant.

2

## Why should we not use OLS estimators in heteroscedastic models?

### As variance terms are inconsistent, the standard error terms calculated often come out to be too small. The OLS estimators are no longer efficient.

3

## How do we calculate the standard error of heteroscedastic models given OLS estimators are inefficient?

###
- Use GLS estimators

- Use OLS to estimate model but then deal with standard errors differently. (ALWAYS use heteroscedastic-robust standard errors in these models).

4

## What is a confidence interval?

### This is a range of values that we are certain that the true data values lie in.

5

## What is hypothesis testing?

### This is when we propose a question of whether one variable will affect the other. It uses the information that we have about a population to try and estimate the relationship in a sample size.

6

## What is the null hypothesis?

###
A specific estimate of the value of the regression parameter.

This differs from the alternative hypothesis which is just another specific estimate - if B1 value is less than null, then left-tailed. The inverse is true.

If B1 is just shown as not equal to null, then there are two sides alternative hypothesis.

7

## What can we use to determine if we should accept or reject the null hypothesis?

###
We should use the test statistic. If alternative hypothesis is true, then test statistic will be very large or very small. (range of values is called the rejection region).

One-sided test and both sided tests can be used. This i when null hypothesis is found to be greater than or less than t statistic.

8

## What does the p-value tell us?

###
This tells us the likelihood of an observed data point happening by chance - the lower the p-value, the likelier it is for the alternative hypothesis to hold true.

Therefore, if the p value is less than the significance level (a), then the null hypothesis should be rejected. The inverse is true.

To calculate p value of a two sided graph, multiply p value by 2.

9

## What is the significance level?

###
This is the probability of rejecting the null hypothesis when it is true. A significance level of 0.05 indicates that there is a 5% probability that a different value

exists.

10

## What are the critical regions?

###
These are the areas of the graph (sample mean) that could be found (usually with low %).

When a null hypothesis is rejected, that value does not fall within the critical region(s).

11