Testing R.docx
This document was uploaded by user and they confirmed that they have the permission to share it. If you are author or own the copyright of this book, please report to us by using this DMCA report form. Report DMCA
Overview
Download & View Testing R.docx as PDF for free.
More details
- Words: 262
- Pages: 2
data<-read_excel("C:/Users/E5/Desktop/DATA JOURNAL.xlsx") > data # A tibble: 18 x 3 observation Salesperson `New Business Ratio`
1 1 0.42 0.65 2 2 0.46 0.62 3 3 0.79 0.81 4 4 0.88 1.5 5 5 0.89 1.38 6 6 0.96 0.93 7 7 0.96 1 8 8 0.96 1.42 9 9 1.3 2.2 10 10 1.52 2 11 11 1.68 1.28 12 12 1.68 1.42 13 13 1.68 2.42 14 14 1.71 1.35 15 15 1.81 1.62 16 16 1.83 0.81 17 17 1.96 1.3 18 18 1.96 1.35 > data<-read_excel("C:/Users/E5/Desktop/DATA JOURNAL.xlsx") > data # A tibble: 18 x 3 observation Salesperson NewBusinessRatio
1 1 0.42 0.65 2 2 0.46 0.62 3 3 0.79 0.81 4 4 0.88 1.5 5 5 0.89 1.38 6 6 0.96 0.93 7 7 0.96 1 8 8 0.96 1.42 9 9 1.3 2.2 10 10 1.52 2 11 11 1.68 1.28 12 12 1.68 1.42 13 13 1.68 2.42 14 14 1.71 1.35 15 15 1.81 1.62 16 16 1.83 0.81 17 17 1.96 1.3 18 18 1.96 1.35 > data2<-lm(Salesperson~NewBusinessRatio,data = data) > summary(data2) Call: lm(formula = Salesperson ~ NewBusinessRatio, data = data) Residuals: Min 1Q Median -0.5580 -0.4038 -0.1428 Coefficients:
3Q 0.3940
Max 0.7763
Estimate Std. Error t value Pr(>|t|) (Intercept) 0.6706 0.3222 2.081 0.0538 . NewBusinessRatio 0.4729 0.2264 2.089 0.0530 . --Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.4697 on 16 degrees of freedom Multiple R-squared: 0.2143, Adjusted R-squared: 0.1652 F-statistic: 4.364 on 1 and 16 DF, p-value: 0.05304
1 1 0.42 0.65 2 2 0.46 0.62 3 3 0.79 0.81 4 4 0.88 1.5 5 5 0.89 1.38 6 6 0.96 0.93 7 7 0.96 1 8 8 0.96 1.42 9 9 1.3 2.2 10 10 1.52 2 11 11 1.68 1.28 12 12 1.68 1.42 13 13 1.68 2.42 14 14 1.71 1.35 15 15 1.81 1.62 16 16 1.83 0.81 17 17 1.96 1.3 18 18 1.96 1.35 > data<-read_excel("C:/Users/E5/Desktop/DATA JOURNAL.xlsx") > data # A tibble: 18 x 3 observation Salesperson NewBusinessRatio
1 1 0.42 0.65 2 2 0.46 0.62 3 3 0.79 0.81 4 4 0.88 1.5 5 5 0.89 1.38 6 6 0.96 0.93 7 7 0.96 1 8 8 0.96 1.42 9 9 1.3 2.2 10 10 1.52 2 11 11 1.68 1.28 12 12 1.68 1.42 13 13 1.68 2.42 14 14 1.71 1.35 15 15 1.81 1.62 16 16 1.83 0.81 17 17 1.96 1.3 18 18 1.96 1.35 > data2<-lm(Salesperson~NewBusinessRatio,data = data) > summary(data2) Call: lm(formula = Salesperson ~ NewBusinessRatio, data = data) Residuals: Min 1Q Median -0.5580 -0.4038 -0.1428 Coefficients:
3Q 0.3940
Max 0.7763
Estimate Std. Error t value Pr(>|t|) (Intercept) 0.6706 0.3222 2.081 0.0538 . NewBusinessRatio 0.4729 0.2264 2.089 0.0530 . --Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.4697 on 16 degrees of freedom Multiple R-squared: 0.2143, Adjusted R-squared: 0.1652 F-statistic: 4.364 on 1 and 16 DF, p-value: 0.05304
Related Documents
Testing
July 2020 14
Testing
May 2020 16
Testing
June 2020 24
Testing
October 2019 41
Testing
April 2020 12
Testing
August 2019 19More Documents from "Saad Bin Farooq Rana"
3_31_2019_detecting .pdf
October 2019 14
Testing R.docx
October 2019 13
Case Study.docx
October 2019 23
Data.pdf
October 2019 22
Report Project 1.docx
October 2019 13