- What are the assumptions of regression?
- What does Heteroskedasticity mean?
- What is the difference between 1st conditional and 2nd conditional?
- What is the example of first conditional?
- Why is OLS unbiased?
- How do you interpret OLS results?
- What is the first conditional used for?
- How do you teach first conditional form?
- What happens if OLS assumptions are violated?
- What is conditional independence?
- What are the least squares assumptions?
- How do you explain first conditional?
- What comes first in a conditional statement?
- What is an example of a conditional sentence?
- Why is the mean of the error term zero?
- What does a regression mean?
- What is the example of third conditional?
- What is the zero conditional?

## What are the assumptions of regression?

There are four assumptions associated with a linear regression model: Linearity: The relationship between X and the mean of Y is linear.

Homoscedasticity: The variance of residual is the same for any value of X.

Independence: Observations are independent of each other..

## What does Heteroskedasticity mean?

In statistics, heteroskedasticity (or heteroscedasticity) happens when the standard deviations of a predicted variable, monitored over different values of an independent variable or as related to prior time periods, are non-constant.

## What is the difference between 1st conditional and 2nd conditional?

1. The first conditional describes something that is possible, and could really happen. 2. The second conditional describes something that is possible, but will almost certainly not happen.

## What is the example of first conditional?

Using the first conditionalExampleExplanationIf it is sunny tomorrow, I will have a picnic.It is possible that it will be sunny tomorrow. In this condition I will have a picnic..If you come to the party, I will be very happy.It is possible that you will come to the party. In this condition I will be very happy.3 more rows•Jul 5, 2009

## Why is OLS unbiased?

In statistics, ordinary least squares (OLS) is a type of linear least squares method for estimating the unknown parameters in a linear regression model. Under these conditions, the method of OLS provides minimum-variance mean-unbiased estimation when the errors have finite variances. …

## How do you interpret OLS results?

Statistics: How Should I interpret results of OLS?R-squared: It signifies the “percentage variation in dependent that is explained by independent variables”. … Adj. … Prob(F-Statistic): This tells the overall significance of the regression. … AIC/BIC: It stands for Akaike’s Information Criteria and is used for model selection.More items…•

## What is the first conditional used for?

The first conditional is a linguistic structure which is used to express a consequence or result in the future due to a specific situation in present that is being accomplished or not.

## How do you teach first conditional form?

Here are the steps to teaching the first conditional form:Introduce the construction of the first conditional: If + present simple + (then clause) future with “will.”Point out that the two clauses can be switched: (then clause) future with “will” + if + present simple.More items…•

## What happens if OLS assumptions are violated?

The Assumption of Homoscedasticity (OLS Assumption 5) – If errors are heteroscedastic (i.e. OLS assumption is violated), then it will be difficult to trust the standard errors of the OLS estimates. Hence, the confidence intervals will be either too narrow or too wide.

## What is conditional independence?

From Wikipedia, the free encyclopedia. In probability theory, a random variable Y is said to be mean independent of random variable X if and only if its conditional mean E(Y | X=x) equals its (unconditional) mean E(Y) for all x such that the probability that X = x is not zero.

## What are the least squares assumptions?

The Least Squares AssumptionsUseful Books for This Topic: … ASSUMPTION #1: The conditional distribution of a given error term given a level of an independent variable x has a mean of zero. … ASSUMPTION #2: (X,Y) for all n are independently and identically distributed. … ASSUMPTION #3: Large outliers are unlikely.More items…•

## How do you explain first conditional?

First conditional is used to talk about actions/events in the future which are likely to happen or have a real possibility of happening.If it rains tomorrow, I’ll stay at home.If my father doesn’t buy me a bike for my birthday, I will be very unhappy.

## What comes first in a conditional statement?

The if-clause contains the condition (the event or situation that must happen first), and the main-clause, which is the result. The two events are connected. One event or situation is a condition for another event or situation. Learn more: What are conditional sentences?

## What is an example of a conditional sentence?

A conditional sentence tells what would or might happen under certain conditions. It most often contains an adverb clause beginning with ‘if’ and an independent clause. … For example: “If it’s cold, I’ll wear a jacket” or “I’ll (I will) wear a jacket if it’s cold.” Either clause can go first.

## Why is the mean of the error term zero?

OLS Assumption 2: The error term has a population mean of zero. The error term accounts for the variation in the dependent variable that the independent variables do not explain. … For your model to be unbiased, the average value of the error term must equal zero.

## What does a regression mean?

Regression is a statistical method used in finance, investing, and other disciplines that attempts to determine the strength and character of the relationship between one dependent variable (usually denoted by Y) and a series of other variables (known as independent variables).

## What is the example of third conditional?

If it had rained, you would have gotten wet. You would have gotten wet if it had rained. You would have passed your exam if you had worked harder. If you had worked harder, you would have passed your exam.

## What is the zero conditional?

We use the zero conditional when we want to talk about facts or things that are generally true. Scientific facts are often covered by the zero conditional: “When you heat ice, it melts.” The zero conditional uses if or when and must be followed by the simple present or imperative.