#require is used inside functions, as it outputs a warning and continues if the package is not #found, whereas library will throw an error.
require(mosaic)
require(readr)
require(mosaic)
require(dplyr)
require(lattice)
require(graphics)
Read the Popcorn data set into your R session and attach it:
#note below command requires loading package readr
Popcorn <- read_csv("P:/SUNY-Brockport/SUNY Brockport_1/teaching/Staitstical Methods/Spring2018/Ch4ANOVA/Ch4/Popcorn.csv")
View(Popcorn) #comment it while knitting, as you dont want it to pop up while creating html
Compute descriptive statistics by group and/or factor level, old school
attach(Popcorn)
mean(PopRate[Brand=="Fastco"])
## [1] 81.75507
#Calculate means by factor level, another way
meanF <- mean(Popcorn[Brand=="Fastco",]$PopRate)
mean(PopRate[Brand=="Pop Secret"])
## [1] 80.93226
mean(PopRate[Time==105])
## [1] 78.28701
mean(PopRate[Time==135])
## [1] 84.40032
mean(PopRate)
## [1] 81.34367
Quick and easy way using package mosaic
attach(Popcorn)
mean(PopRate~Brand)
## Fastco Pop Secret
## 81.75507 80.93226
mean(PopRate~Time)
## 105 135
## 78.28701 84.40032
mean(PopRate~Microwave)
## Lounge Room
## 80.42122 82.26611
mean(PopRate)
## [1] 81.34367
#The average popping rates for each level of Brand and Time
mean(PopRate~Brand+Time)
## Fastco.105 Pop Secret.105 Fastco.135 Pop Secret.135
## 81.13192 75.44209 82.37821 86.42244
#The average popping rates for each level of Brand,microwave and Time
mean(PopRate~Brand+Time+Microwave)
## Fastco.105.Lounge Pop Secret.105.Lounge Fastco.135.Lounge
## 81.40000 72.19525 81.85560
## Pop Secret.135.Lounge Fastco.105.Room Pop Secret.105.Room
## 86.23405 80.86385 78.68892
## Fastco.135.Room Pop Secret.135.Room
## 82.90082 86.61083
Find the difference between average PopRate for the cooking times for each brand:
mean(PopRate[(Brand=="Fastco") & (Time==135)])-mean(PopRate[(Brand=="Fastco") & (Time==105)])
## [1] 1.246288
mean(PopRate[(Brand=="Pop Secret") & (Time==135)])-mean(PopRate[(Brand=="Pop Secret") & (Time==105)])
## [1] 10.98035
attach(Popcorn)
# In order to do anova, we have to make Time into a categorical variable
#Thus, using as.factor we can transform the data
Time1 <- as.factor(Time)
mutate(Popcorn,Time1) #if it doesnt work on your ocmputer, use cbind.data.frame
## # A tibble: 32 x 6
## Brand Microwave Time `Unpopped (percent)` PopRate Time1
## <chr> <chr> <int> <dbl> <dbl> <fctr>
## 1 Fastco Lounge 105 17.40 82.6000 105
## 2 Fastco Lounge 105 12.50 87.5000 105
## 3 Fastco Lounge 105 24.70 75.3000 105
## 4 Fastco Lounge 105 19.80 80.2000 105
## 5 Fastco Room 105 26.20 73.8000 105
## 6 Fastco Room 105 22.40 77.6000 105
## 7 Fastco Room 105 11.50 88.5000 105
## 8 Fastco Room 105 16.44 83.5554 105
## 9 Fastco Lounge 135 18.93 81.0667 135
## 10 Fastco Lounge 135 9.20 90.8000 135
## # ... with 22 more rows
plotPoints(PopRate~Time1|Brand)
xyplot(PopRate~Time1|Brand) # will do the same
Note on when to use what kind of graph
- Only Categorical Variables: Bargraph
- One Numeric Variable (can also have one categorical grouping variable): Histogram or Boxplot
- Two Numeric Variables: Scatterplot
attach(Popcorn)
bwplot(PopRate~Time1|Brand)
#The two-way ANOVA is conducted using the aov() command.
attach(Popcorn)
## The following objects are masked from Popcorn (pos = 3):
##
## Brand, Microwave, PopRate, Time, Unpopped (percent)
## The following objects are masked from Popcorn (pos = 4):
##
## Brand, Microwave, PopRate, Time, Unpopped (percent)
## The following objects are masked from Popcorn (pos = 5):
##
## Brand, Microwave, PopRate, Time, Unpopped (percent)
## The following objects are masked from Popcorn (pos = 6):
##
## Brand, Microwave, PopRate, Time, Unpopped (percent)
pop.aov1 <- aov(PopRate~Brand+Time+Brand:Time) #store the ANOVA results in object pop.aov1
summary(pop.aov1) #Use the summary() command to obtain the ANOVA table:
## Df Sum Sq Mean Sq F value Pr(>F)
## Brand 1 5.4 5.42 0.131 0.7204
## Time 1 299.0 298.98 7.219 0.0120 *
## Brand:Time 1 189.5 189.50 4.575 0.0413 *
## Residuals 28 1159.7 41.42
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
interaction.plot(Brand, Time1, PopRate, main= "Brand Time Interaction") # Brand Time interaction plots
interaction.plot(Brand, Microwave, PopRate,main= "Brand Microwave Interaction") # Brand Microwaveinteraction plots
interaction.plot(Time, Microwave, PopRate, main="Time Microwave Interaction") # Time Microwave interaction plots
