Question

A marketing firm gathered the following data on popup ads received in an hour of screen time on I-phones and Samsung phones for 12 individuals to determine if there is a difference in the number of ads received.

Number of ads	Type of phone
20	I-phone
25	Samsung
15	I-phone
30	Samsung
35	Samsung
25	I-phone
40	Samsung
10	I-phone
30	Samsung
35	I-phone
20	Samsung
15	I-phone

1. What are the independent and dependent variables?
2. Calculate the Total Variation (SST), Unaccountable Variation (SSunacct), and Accountable Variation (SSacct) for these data.
3. Calculate eta square and give a verbal interpretation of eta square.
4. Calculate the standard deviation for each type of phone assuming these are sample data.
5. Draw a simple bar chart illustrating the data.
6. Does there appear to be a difference in the number of ads received? Describe your reasoning.

Answer 1

a. Independent variable=Type of phone; Dependent variable=An hour of screen time

b.

Anova: Single Factor
SUMMARY
Groups	Count	Sum	Average	Variance
I-phone	6	120	20	80
Samsung	6	180	30	50
ANOVA
Source of Variation	SS	df	MS	F	P-value	F crit
Between Groups	300	1	300	4.615385	0.057224	4.964603
Within Groups	650	10	65
Total	950	11

SST=950, SSunacct=650, and SSacct=300.

c. eta square=SSacct/SST=300/950=0.3158 i.e. 31.58% of total variation in hour of screen time is explained by type of phone.

d. Standard deviation for I-phone=8.9443; Standard deviation for Samsung=7.0711.

e.

f. Since p-value=0.057224>0.05, there is insignificant difference in the number of ads received.