class: center, middle, inverse, title-slide .title[ #
Cali Housing Market
] .subtitle[ ##
] .author[ ###
Jessica Gorr
] .institute[ ###
West Chester University of Pennsylvania
] .date[ ###
Prepared for
STA533: HTML Presentation
Slides available at:
https://rpubs.com/jgorr01
AND
https://github.com/jessgorr01/jGorrCV
] --- class:inverse4, top <h1 align="center"> Table of Contents</h1> <BR> .pull-left[ - Data background - searchable table - Model Building - R code - SLR Assumptions - Normality - Independence - Homoscedasticity -Linearity - Analysis - Model Fit - written Analysis - Conclusion ] --- <h1 align = "center">CA Housing Price Data <font color="orange">Search Table</font></h1> <BR>
--- <h1 align = "center">Key <font color="orange">Variables</font></h1> <BR> .pull-left[ - Explanatory - median_income <br><br> <center> <img src="img/money.gif" width=300 height=200> </center> ] .pull-right[ - Response - median_house_value <br><br> <center> <img src="img/housing.gif" width=300 height=200> </center> ] --- name:model building <h1 align="center"> Model <font color="orange">Building and Formula</font></h1> <br> ```r house <- read.csv("ca-housing-price.csv") mod = lm(formula = median_house_value ~ median_income, data = house) ``` <br> <center> `\(y=\beta_0+\beta_1x_1+\epsilon\)`, where `\(\epsilon \sim N(0, \sigma^2)\)`. <br> `\(MedianHouseValue=\beta_0+\beta_1*MedianIncome+\epsilon\)`.</center> --- <h1 align="center"> Model <font color="orange">Summary and CV</font></h1> ``` ## ## Call: ## lm(formula = median_house_value ~ median_income, data = house) ## ## Residuals: ## Min 1Q Median 3Q Max ## -540697 -55950 -16979 36978 434023 ## ## Coefficients: ## Estimate Std. Error t value Pr(>|t|) ## (Intercept) 45085.6 1322.9 34.08 <2e-16 *** ## median_income 41793.8 306.8 136.22 <2e-16 *** ## --- ## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 ## ## Residual standard error: 83740 on 20638 degrees of freedom ## Multiple R-squared: 0.4734, Adjusted R-squared: 0.4734 ## F-statistic: 1.856e+04 on 1 and 20638 DF, p-value: < 2.2e-16 ``` ``` ## [1] 40.48116 ``` ``` ## 2.5 % 97.5 % ## median_income 41192.49 42395.21 ``` --- <h1 align="center"> Simple Linear Regression Assumptions - <font color="orange">Linearity</font></h1> <img src="GorrSLR_files/figure-html/unnamed-chunk-4-1.png" width="600px" style="display: block; margin: auto;" /> --- <h1 align="center"> Assumptions Continued - <font color="orange">Normality</font></h1> <img src="GorrSLR_files/figure-html/unnamed-chunk-5-1.png" width="600px" /> --- <h1 align="center"> Cont. - <font color="orange">Homoscedasticity & Independence</font></h1> <img src="GorrSLR_files/figure-html/unnamed-chunk-6-1.png" width="600px" /> --- <h1 align="center"><font color="orange">Conclusion</font></h1> <center> <br><br> <img src="img/market.jpg" width=300 height=200> </center> <br><br><br> <h1 align="center">Thank You!</h1>