## CHECK THESE SAMPLES OF Multiple Linear Regression Analysis

...? Investigating the determinants of property crime in the United s Introduction This report is an investigation of the determinants of property crimes in the United States. By property crimes, typically the references is to burglary, larceny, theft and motor vehicle theft. We seek to gain an understanding of what socio-economic characteristics of a particular state make it more susceptible to a larger number of property crimes. Data and methodology By using **multiple** **regression** **analysis**, the report is in pursuit of obtaining statistical evidence for or against commonly held beliefs regarding causality of various factors and crime. We use a State-wide data set that includes a record of...

6 Pages(1500 words)Essay

...?**Multiple** **Regression** 0 General Purpose **Multiple** **regression** is simply an extension of **linear** **regression**, a statistical process which seeks to find the **linear** relationship between an independent variable and a dependent variable. In the case of **multiple** **regression**, the main purpose is to find the **linear** relationship between the dependent variable and a number of independent variables (Yan & Su, 2009). **Multiple** **regression** is one of the most widely used tools in statistical **analysis** because it is a very good reflection of...

20 Pages(5000 words)Term Paper

.... Minitab was used to perform **multiple** **regression** **analysis**. It was found that only two variables had a significant relationship with the variable crime rates: dropouts and urban. It was found that as percentage of dropouts increased, the crime rate per thousand inhabitants also increased. It is also evident from the data set that urban areas are having higher crime rates as compared to rural areas. Other variables included in the study did not have much impact on the dependent variable. Introduction Property crimes in an area can be thought of function of many factors. Some of these factors along with hypothesized direction of the relation are: State – different states will have different...

6 Pages(1500 words)Term Paper

...? **Multiple** **Regression** Below is the data that I have been collecting to There is a difference between simple **regression** and **multiple** **regression**. Simple **regression** **analysis** is used to establish the relationship between one variable and the other. One set of the variables is the dependent variable and the other set is the independent variable. The independent variable changes and in turn affects the dependent variable. Simple **regression** is used to establish whether or not indeed the independent variable determines the change that takes place in the dependent variable. It is also used to establish the way in...

2 Pages(500 words)Coursework

...**Multiple** **Regression** **Multiple** **Regression** is a tool which involves a single dependent variable and two or more independent variables. The general form of the **multiple** **regression** is Y= a +b1X1 +b2X2+b3X3...+bnXn + e which can be estimated by Y= a +b1X1 +b2X2+b3X3...+bnXn, where a is the intercept and bi's are the partial **regression** coefficients.
The various statistics associated with **Multiple** **Regression** are
**Regression** Coefficient: The estimated parameter of b
Standard Error of Estimate:
Is the standard deviation of the actual values of Y from the predicted values of...

10 Pages(2500 words)Essay

...**Linear** **Regression** and **Regression** **Analysis** **Regression** is a technique in statistics that enables estimation of the relation existing among variables. The technique seeks to estimate the strength of the relationship between one variable with another or a set of variables. However, when applying this technique, the statistician makes assumptions with regard to the variables and their relationship. **Regression** is based on the assumptions that there exists a **linear** relationship between the involved variables and that they have an additive relationship. There are many **regression** techniques one of them being...

2 Pages(500 words)Assignment

...**Multiple** **regression** **analysis**: Factors affecting economic growth November 28, **Multiple** **regression** **analysis**: Factors affecting economic growth
Executive summary
Economic growth is one of the significant factors to governments’ responsibilities. Existing literature suggests that factors such as labor force, foreign direct investment, and foreign trade influence economic growth. This report investigated relationship between economic capacity (measured through gross domestic product) and the factors. Using data from the Central Intelligence Agency and Excel for data **analysis**, the report identifies positive effects of labor...

3 Pages(750 words)Statistics Project

...**Multiple** **Linear** **Regressions** al Affiliation: **Multiple** **Linear** **Regressions** Types of F test The two types of F test are Type and Type 3. Type I is called the sequential sum of squares. It is used for testing the main effect of the first factor followed by the second factor and then the interaction effect. Type 3 test identifies the presence of main effects followed by the interaction of these effects.
2. R2 and adjusted R2
R2 measures the proportion of the variation on the dependent variable which is explained by the independent variable in a **linear** **regression** model. It also measures how best the...

1 Pages(250 words)Assignment

...whether the **multiple** **linear** **regression** model provided a better description of the relationship between the wave modes than would a **linear** **regression** model with only a **linear** predictor.
**Analysis**
In the model, y (the response) is the ISOw (westward moving intraseasonal modes) and x (the predictor variable) is the ISOe (eastward moving intraseasonal modes). ISOe is further broken down to into more variables by applying power functions of the predictor variable to create a polynomial. Higher power terms are included in the model in order to seek evidence of any improvements in how they increase the accuracy of how wave...

8 Pages(2000 words)Assignment

...Equation
Income = +0.63123236633544 Age +1.6310151733801 Educ +0.6060166606298 HRS +0.72543207253468
Variable
Parameter
S.E.
T-STAT
H0: parameter = 0
2-tail p-value
1-tail p-value
Age[t]
0.631232
0.186068
3.392487
0.000793
0.000397
Educ[t]
1.631015
0.202738
8.044927
0
0
HRS[t]
0.606017
0.178607
3.393018
0.000792
0.000396
Constant
0.725432
0.467417
1.552001
0.1218
0.0609
Variable
Partial Correlation
Age[t]
0.199383
Educ[t]
0.434562
HRS[t]
0.199413
Constant
0.092682
Critical Values (alpha = 5%)
1-tail CV at 5%
1.65
2-tail CV at 5%
1.96
**Multiple** **Linear** **Regression** - **Regression** Statistics
**Multiple** R
0.501424
R-squared
0.251426
Adjusted...

1 Pages(250 words)Case Study