Preference

STEP 1

We are testing to see if pictures of animals have an impact on consumer preference of products.

STEP 2

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

STEP 3

The data is organized into two columns, Preference and Primed, and 42 rows that distinguish the Preference.

STEP 4

The purpose of this study is to determine if pictures of animals on labels or products influence the consumer’s preference of the product.

STEP 5

library(ggplot2)
ggplot(data=preference, mapping=aes(x=preference, y=primed)) + geom_point()

STEP 6

The plot shows there is a dramatic preference in labels. When consumers are primed, they choose the label with the animal, when they are not, they do not choose the label with the animal on it.

STEP 7

Null Hypothesis: Priming the consumer will not influence the preference of label.

STEP 8

Alternative Hypothesis: Priming the consumer will not influence the preference of the label (<,>).

STEP 9

A Matched Paired T-procedure meets all the conditions for a matched pairs t-procedure, paired data and random sampling. Preference meets all of these requirements.

STEP 10

This test will help further determine if there is any correlation between the data sets.

STEP 11

ggplot(data=preference) + geom_qq(mapping = aes(sample=preference, color=primed))

STEP 12

The traditional level of significance for this test, 0.05 or 5%, will what we use.

STEP 13

t.test(formula=preference~primed, data=preference)

## 
##  Welch Two Sample t-test
## 
## data:  preference by 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

STEP 14

The p-value is 0.002666, meaning that the data is not significant, and that it is smaller than the level of significance.

STEP 15

The confidence interval is not equal to zero.

STEP 16

The means of the samples are not equal because the confidence interval is not equal to zero and the p-value is smaller than the level of significance.

STEP 17

We can conclude that there is no difference in the preference of labels between consumers who were primed and not primed. We can accept the null hypothesis and reject the alternative hypothesis.