Write a clear conclusion regarding the association between height in inches and weight in pounds, using the multivariate model results
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
Write a clear conclusion regarding the association between height in inches and weight in pounds, using the multivariate model results
![### Regression Analysis Table
This table presents the results of a regression analysis, examining the relationship between several independent variables and the dependent variable: weight in pounds.
#### Model Summary
- **Dependent Variable**: Weight - Pounds (PUF Recode)
#### Table Columns Explained
- **Unstandardized Coefficients (B)**: Represents the change in the dependent variable for a one-unit change in the independent variable.
- **Std. Error**: The standard error of the coefficient, indicating the variability of the coefficient estimate.
- **Standardized Coefficients (Beta)**: Shows the effect size in terms of standard deviation units.
- **t**: The t-statistic for testing the null hypothesis that the coefficient is equal to zero.
- **Sig.**: The p-value indicating the significance of the relationship, with values below 0.05 typically considered significant.
- **95.0% Confidence Interval for B**: The range in which the true population parameter is expected to fall 95% of the time.
#### Independent Variables
1. **(Constant)**
- **B**: -134.491
- **Std. Error**: 18.600
- **t**: -7.231
- **Sig.**: 0.000
- **95% Confidence Interval**: [-171.045, -97.936]
2. **Height - Inches (PUF Recode)**
- **B**: 4.100
- **Std. Error**: 0.281
- **Beta**: 0.569
- **t**: 14.592
- **Sig.**: 0.000
- **95% Confidence Interval**: [3.548, 4.652]
3. **# Cans of Soda w/Sugar Drunk Yesterday (PUF 1 Yr Recode)**
- **B**: 4.179
- **Std. Error**: 1.909
- **Beta**: 0.085
- **t**: 2.189
- **Sig.**: 0.029
- **95% Confidence Interval**: [0.428, 7.929]
4. **Usual Source of Care Other Than ER**
- **B**: -0.945](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Ff19c1f26-9983-41eb-bb8c-6870b1819c87%2F5a77f319-5fcd-4ea5-87c8-d40ab2f1d913%2Fexy8yf8_processed.png&w=3840&q=75)
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