Toggle navigation
Ask Questions
Ask
Answer Questions
Answer
Users
FAQ
Login
Register
Preview 50% of the Answer Below
Due to formatting, images, tables, or paragraphs may be out of place or not shown. Rest assured that they will be included and formatted correctly in your purchased answer.
Details
Question Title:
Calories and SaltThe data set shown below gives
Go Back to the Question
Answer Preview
</p> <p>The XXXXXXXXXXX between Sodium and Calories XX X.XX (0.8634031). </p> <p>XXX XXXXXXX plot XXXXX that the hot XXXX with more calories XXXX XXXX more sodium. Generally, with 1 XXXX XXXXXXXX in XXXXXXXX, XXX amount of XXXXXX will increase X.XXX mg. There XXXXX to XX XXX XXXXXXX (XXX, XXX). </p> <p>The correlation XXXXXXXXXXX XXXXXXXX that there is a strong XXXXXXXX correlation XXXXXXX calories and sodium. So it supports XX XXXXXXXX. Besides, the p-XXXXX of XXX XXXXXXXXXX model XX X.04e-06, which XXXXXXXX that XXXXXXXX significantly correlated with sodium. </p> <p>XXXX XXX outlier XXX XXXXXXX, the model XXXXXXX </p> <p>y= 46.X+2.XXXX </p> <p>XXX XXX scatter XXXX is </p> <p><XXX XXX="file:///C:\Users\uqzqiao1\AppData\XXXXX\XXXX\msohtmlclip1\XX\clip_image004.jpg" width="602" height="XXX"> </p> <p>XXX correlation between Sodium and XXXXXXXX becomes 0.83 (X.8338989). </p> <p>The XXX XXXX still XXXXX that XXX hot XXXX with XXXX calories will XXXX more sodium. XXXXXXXXX, XXXX X XXXX increase in Calories, the amount of XXXXXX will increase 2.XXX XX. </p> <p>XXX correlation XXXXXXXXXXX still suggests XXXX XXXXX XX a XXXXXX positive correlation XXXXXXX XXXXXXXX and sodium. The XXX p-XXXXX of the XXXXXXXXXX model is X.XXX-05, XXXXX XXXXX XXXXXXXX that XXXXXXXX XXXXXXXXXXXXX correlated with XXXXXX. So it XXXXX supports XX XXXXXXXX. </p> <p>XXX analyses robustly XXXXXXXXX that hot XXXX with XXXX XXXXXXXX will XXXX XXXX sodium. XX XXXXX XXXXX, XXXXX is a strong XXXXXXXXXXX between XXXXX two XXXXXXXXX. XXXXXXX, XX XXXXXX reach the conclusion XXXX there is a XXXXXX relationship between these two XXXXXXXXX. The XXXXXXXXXXX XXXXXXX XXXX XXX result XXXX a XXXXXXXX XXXXXXXXXXX from a XXXXXXXXXXX/XXXXXX XXXXXXXX XXXXX XXXXXXXXXX with these two variables, respectively. XXXXXXX, XXXX there XX a casual relationship between these XXX XXXXXXXXX, the direction is hard XX XXXXXXX. </p> <p> </p> <p>########################X XXXX </p> <p>#Prepare XXXX </p> <p>x=read.table("data", XXXXXX=X) </p> <p>XXXXXXXX(x)=c("Brand", "XXXXXXXX", "XXXXXX") </p> <p>#Linear regression (XXX) </p> <p>XXXXX=XX(Sodium~XXXXXXXX, data=x) </p> <p>#XXXXXXX plot </p> <p>XXXX(x$XXXXXXXX, x$Sodium, XXX=16, XXX = 1.3, col = "blue", </p> <p> XXXX = "XXXXXX XXXXXXX CALORIES", ylab="Sodium (mg)", XXXX="Calories") </p> <p>abline(model) </p> <p>#Correlation XXXXXXXXXXX </p> <p>XXX(x$XXXXXX, x$XXXXXXXX) </p> <p> </p> <p># Remove outlier </p> <p>x2=x[-XX,] </p> <p># XXXXX </p> <p>XXXXX=lm(XXXXXX~XXXXXXXX, XXXX=XX) </p> <p>#XXXXXXX XXXX </p> <p>plot(x2$Calories, x2$Sodium, pch=16, XXX = X.3, col = "XXXX", </p> <p> main = "XXXXXX AGAINST XXXXXXXX", XXXX="XXXXXX (mg)", XXXX="Calories") </p> <p>XXXXXX(XXXXX) </p> <p>#Correlation XXXXXXXXXXX </p> <p>cor(XX$Sodium, x2$XXXXXXXX) </p> <p></p>">
Attachment #1 Preview
