We will utilize statistical data to investigate if consumers who are primed have a higher interest in a product than those who are unprimed.
preference<- read.csv("preference.csv")
preference
## preference primed
## 1 1.8 0
## 2 0.1 0
## 3 4.0 0
## 4 2.1 0
## 5 2.4 0
## 6 3.4 0
## 7 1.7 0
## 8 2.2 0
## 9 1.9 0
## 10 1.9 0
## 11 0.1 0
## 12 3.3 0
## 13 2.1 0
## 14 2.0 0
## 15 1.4 0
## 16 1.6 0
## 17 2.3 0
## 18 1.8 0
## 19 3.2 0
## 20 0.8 0
## 21 1.7 1
## 22 1.7 1
## 23 4.2 1
## 24 3.0 1
## 25 2.9 1
## 26 3.0 1
## 27 4.0 1
## 28 4.1 1
## 29 2.9 1
## 30 2.9 1
## 31 1.2 1
## 32 4.0 1
## 33 3.0 1
## 34 3.9 1
## 35 3.1 1
## 36 2.5 1
## 37 3.2 1
## 38 4.1 1
## 39 3.9 1
## 40 1.1 1
## 41 1.9 1
## 42 3.1 1
library(ggplot2)
A research team randomly assigned participants to either a primed condition (denoted 1 in the data set) or non-primed condition (denoted 0). Each participant was asked to indicate their attitude toward a product on a continuous rating scale ranging from 0 (dislike very much) to 6 (like very much). A bottle of pet shampoo with a picture of a collie on the label was the product. Prior to giving their score, however, participants were asked to do a word find where four of the words were common across groups (pet, grooming, bottle, label) and four were either related to the image (dog, collie, puppy, woof for the primed group) or image conflicting (cat, feline, kitten, meow for the non-primed group). Responses on 44 individuals (20 in the non-primed group and 22 in the primed group) were recorded to one decimal place.
The purpose of this study is to indicate if consumers who are primed have a higher interest in the product than those who are not primed.
library(ggplot2)
ggplot(data=preference, mapping=aes(x=as.factor(primed), y=preference)) + geom_point()
The people that were primed have a higher preference for the product than the people that were not primed.
There is no difference in preference of the product between the subjects that were primed, and the subjects that were not primed. In other words, consumers who are primed and unprimed will have the same mean.
People that are primed have more of a preference for the product than people that were not primed. In other words, consumers who are primed will have a higher mean than the customers that were not primed.
I am going to run a t-test on this data, which means I will be testing my hypotheses (null and alternative) about population means of a quantitative variable.
Two sample.
library(ggplot2)
ggplot(data=preference) + geom_qq(mapping=aes(sample=preference, color=as.factor(primed)))
I will use the traditional level of significance, 0.05.
t.test(formula=preference~as.factor(primed), data=preference)
##
## Welch Two Sample t-test
##
## data: preference by as.factor(primed)
## t = -3.2072, df = 39.282, p-value = 0.002666
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -1.577912 -0.357543
## sample estimates:
## mean in group 0 mean in group 1
## 2.005000 2.972727
The p value is much less than 0.05, which rejects the null hypothesis.
0 is not present in the range of confidence, so therefore we reject the null hypothesis.
There is a statistically significant different between the primed and not primed group, which means that the primed group showed higher preference to the product than the not primed group.
To conclude, the primed group had a higher preference for the product than the not primed group.