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# We Helped With This R Language Programming Assignment: Have A Similar One?

Category | Programming |
---|---|

Subject | R | R Studio |

Difficulty | Undergraduate |

Status | Solved |

More Info | Statistic Homework Answers |

## Short Assignment Requirements

## Assignment Description

**Objective **

*.*

*In this exercise we **look at multiple predictor linear regression models for a
continuous quantitative dependent (response) variable of interest as a function
of a multiple quantitative independent (predictor, explanatory) variables. We visualize
the potential linear relationship between variables using scatterplots with the
dependent variable on the vertical axis and the independent variable on the
horizontal axis for all combinations of dependent and independent variables. We
also determine the strength and the direction of that linear relationship in
the correlation model by computing a correlation between the dependent and
independent variables. As in a previous unit on ANOVA we will partition the
variation in the dependent variable into a regression model (explained)
variation, and an error or unexplained variation. The associated ANOVA table
will give us the explanatory power of the model as the coefficient of multiple
determination unadjusted and adjusted for degrees of freedom, or R-squared as
before. We will interpret the software computed statistical significance of the
model parameters (intercept and slopes) and compare those p-values to the
desired level of significance.*

__MUST
USE R and attach file accordingly for the following two problems __

**PROBLEM 1( Attached RISKFACT data in an
excel spreadsheet) **

** Using R software perform an analysis using a sample of
size 30 and an analysis using the entire dataset**. Include scatterplots,
correlation between all variables, regression analysis including ANOVA table.

**(coefficients of multiple determination) and**

__Discuss the predictive power__**using the ANOVA table, and**

__statistical significance of all parameters__**(intercept and slopes) assuming a level of alpha of 0.05.**

__statistical significance of the individual model parameters__

Refer to the data on cardiovascular risk factors (RISKFACT). The subjects are 1000 males

engaged in sedentary occupations. You wish to study the relationships among risk factors in this

population. The variables are

Y = oxygen consumption

X1 = systolic blood pressure (mmHg)

X2 = total cholesterol (mg/dl)

X3 = HDL cholesterol (mg/dl)

X4 = triglycerides (mg/dl)

Select a simple random sample from this population and carry out an appropriate statistical

Analysis.

__MUST
provide a narrative report of your ____findings ____in a word doc__

**PROBLEM 2 ( Attached NCBIRTH800 data in an
excel spreadsheet)**

And using the data from NCBIRTH800, perform the following analysis including your analysis:

a. Fit a multiple predictor
linear regression model using variable **tgrams **as the dependent
(response) variable and variables **weeks **and **gained **as the
independent (predictor, explanatory) variables

b. Comment on the average change
in **tgrams **per **week **and per **gained**.

c. Repeat part (a) but add
qualitative (categorical) independent variables **drink **and **smoke **(chapter
11).

d. Discuss the differences on **tgrams **that variables **drink **and **smoke **have considering the different
combinations of drinking and smoking or not.

e. Include scatterplots, correlation between all variables, regression analysis including ANOVA table. Discuss the predictive power (coefficient of multiple determination) and statistical significance of correlations and of the model parameters (intercept and slopes) assuming a level of alpha of 0.05.

__MUST provide a narrative report of your
findings in a word doc __