Skincare Expenditure Analysis

This assignment delves into the factors that influence individuals' spending on skincare products. It investigates the relationship between demographic characteristics (gender and age) and skincare expenditure. Additionally, it examines whether allergies and income levels play a significant role in shaping spending patterns. The analysis utilizes statistical methods to test hypotheses and provide insights into consumer behavior in the skincare market.

Running head: REASEARCH METHOD
Research Method
Name of the Student
Name of the University
Author note

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Table of Contents
Introduction......................................................................................................................................2
Result from Quantitative analysis....................................................................................................3
Result from Qualitative analysis....................................................................................................11
Discussion......................................................................................................................................12
Appendix........................................................................................................................................14

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Introduction
The report aims to analyze relation between the expenses on different skin care product
and factors such as age of people, their gender and other related factors. Various skin care
product such as cleanser, exfoliate product, sunscreen, moisture are considered. It is generally
asserts that females are likely to spend more on skin care product than their male counterpart.
From this the hypothesis drawn is as follows
Hypothesis 1
Null Hypothesis: There is no significant difference between average expenditure on skin care
product between males and females.
Alternative Hypothesis: The mean expenditure of females on skin care product is greater than
that of expenditure made by males.
The opinion about skin care product and expenses of the product may vary between genders. To
test this assertion following hypothesis testing is performed.
Hypothesis 2
Null hypothesis: There is no significant difference in opinion between male and females
Alternative hypothesis: There is significant difference in opinion depending on gender.
With growing age people are more prone to different skin diseases and this likely to be
increasing their expenditure on skin care expenses. The two relevant hypothesis tested here is the
following.

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Hypothesis 3
Null Hypothesis: There is no significant difference in the expenditure in different age groups
Alternative Hypothesis: The expenditure on skin care product differs significantly among
different age group.
The final hypothesis is derived to test whether presence of allergies have limited the spending on
certain types skin care product.
Hypothesis 4
Null Hypothesis: There is no significant difference in expenditure between groups having
allergies and do not.
Alternative Hypothesis: There is significant difference in expenditure on skin care product.
Result from Quantitative analysis
Table 1: Descriptive Statistics of age
Age
Mean
30.7805
6
Standard Error
0.64112
8
Median 26.5
Mode 22
Standard
Deviation
11.7869
9
Sample Variance
138.933
2
Kurtosis
0.29481
5
Skewness
1.06980
2
Range 55

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Minimum 18
Maximum 73
Sum
10403.8
3
Count 338
1 2
0
50
100
150
200
250
300
Total
Total
Figure 1: Proportion of male and female population
71%
24%
5%
Total
1
2
3

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Figure 2: Distribution of population in different age group
1 2 3
0
20
40
60
80
100
120
140
Total
Total
Figure 3: Frequency of cleaner brand
1 2 3
0
10
20
30
40
50
60
70
Total
Total
Figure 4: Frequency of exfoliate brand

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1 2 3
0
20
40
60
80
100
120
140
Total
Total
Figure 5: Frequency of moisturizer brand
1 2 3
0
20
40
60
80
100
120
140
Total
Total
Figure 6: Frequency of Sunscreen brand

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0-100
101-200
201-300
301-400
401-500
Missing
Figure 7: Distribution of income
Table 2: t test for equality of mean expense between male and female
t-Test: Two-Sample Assuming Equal Variances
male female
Mean 56.48485 85.09225
Variance 4069.484 8767.595
Observations 66 271
Pooled Variance 7856.021
Hypothesized Mean Difference 0
df 335
t Stat -2.35136
P(T<=t) one-tail 0.009642
t Critical one-tail 1.649415
P(T<=t) two-tail 0.019284
t Critical two-tail 1.967071

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Table 3: t test for difference in opinion about price influencing choice of skin care product
t-Test: Two-Sample Assuming Equal Variances
Female Male
Mean 3.443182 3.484375
Variance 1.069003 0.983879
Observations 264 64
Pooled Variance 1.052552
Hypothesized Mean Difference 0
df 326
t Stat -0.28818
P(T<=t) one-tail 0.386697
t Critical one-tail 1.649541
P(T<=t) two-tail 0.773395
t Critical two-tail 1.967268
Table 4: t test for difference in opinion about expensive skin care product are better
t-Test: Two-Sample Assuming Equal Variances
Male Female
Mean
2.98437
5
2.9469
7
Variance 0.93626
0.9021
2
Observations 64 264
Pooled Variance
0.90871
8
Hypothesized Mean Difference 0
df 326
t Stat
0.28162
7
P(T<=t) one-tail
0.38920
4
t Critical one-tail
1.64954
1
P(T<=t) two-tail
0.77840
8
t Critical two-tail
1.96726
8

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Table 5: t test for difference in opinion about looking after the skin is important
t-Test: Two-Sample Assuming Equal Variances (Looking after skin is
important)
Male Female
Mean 3.875 4.390152
Variance 0.68254 0.504998
Observations 64 264
Pooled Variance 0.539308
Hypothesized Mean Difference 0
df 326
t Stat -5.03468
P(T<=t) one-tail 3.97E-07
t Critical one-tail 1.649541
P(T<=t) two-tail 7.93E-07
t Critical two-tail 1.967268
Table 6: t test for difference in opinion about purchasing the product online in available
t-Test: Two-Sample Assuming Equal Variances
Male Female
Mean 3.28125
3.48106
1
Variance 1.443452
0.92739
7
Observations 64 264
Pooled Variance 1.027125
Hypothesized Mean Difference 0
df 326
t Stat -1.41502
P(T<=t) one-tail 0.079009
t Critical one-tail 1.649541
P(T<=t) two-tail 0.158018
t Critical two-tail 1.967268

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Table 7: ANOVA table for testing relation between different age group and expenditure
Anova: Single Factor
SUMMARY
Groups Count Sum Average Variance
1 233 18213 78.16738 7529.45
2 78 6960 89.23077 10627.32
3 18 875 48.61111 1022.958
ANOVA
Source of Variation SS df MS F P-value F crit
Between Groups 24938.53 2 12469.26 1.574032 0.208779 3.023431
Within Groups 2582527 326 7921.861
Total 2607465 328
Table 8: Result of t test analyzing relation between allergies and expenditure
t-Test: Two-Sample Assuming Equal
Variances
1 2
Mean
72.3943
7
81.0387
6
Variance
6042.04
2
8483.89
7
Observations 71 258
Pooled Variance
7961.17
6
Hypothesized Mean Difference 0
df 327
t Stat -0.72291
P(T<=t) one-tail
0.23512
5
t Critical one-tail 1.64952

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7
P(T<=t) two-tail
0.47024
9
t Critical two-tail
1.96724
5
Result from Qualitative analysis
The qualitative analysis is supplement of quantitative analysis. For qualitative analysis
the selected samples are interviewed with pre-designed questionnaire. The aim of this paper is to
determine the factors influencing purchase of skincare products. There is no doubt that price is
the primary determinant of demand. The paper attempts to find out factors other than price
influencing purchasing of skincare product. The first response reveals that review about the
product is an important determinant of purchasing decision. People go through the review made
by other users of the product before making purchase. As the skin care are very sensitive and
tends to have side effects if not chosen suitably. However, the skin types of individual are
different and react differently but customers usually prefer to have a complete knowledge of the
product before making their purchase.
The financial status of individual determines the purchase of skincare product. When
people have extra money then they make purchase of expensive skincare products such as a good
quality serum or eye cream. Serum is considered as a good booster for a healthy skin. On the
other hand if people have less money they try to undercut some expenses of skin care products
and only makes purchase of necessary product. Sunscreen is an essential item in the basket of
skin care products. It protects skin from harmful ultraviolet rays. When people have less mon ey
and has to make choice among essential products. In this situation people choose Sunscreen and
forgo moisturizers to be used in the morning.

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The next concern is regarding how people value their money while purchasing anything
for skincare. In this situation people generally take decision based on price. It is commonly
believed by the people that expensive skincare products are enriched with amazing formula.
Here, the quality of a product and its purchasing decision are driven by the price tag.
There are some products that people use daily and spending on these items is happened to
be greater than others. Two such daily skin care product is sunscreen and toner.
Discussion
In the report a total of 339 people were sampled. Among them the portion of female
population outweighs that of the male population. In the total population 271 respondents are
females while only 66 are males. The sample respondents are then classified in three different
age groups ranging from 18 to 35, 36 to 54 and 55 to 73 denoted as 1, 2 and 3 respectively. Most
of the people belong to first age group having 239 people; the second group has 81 people while
the third group has only 18 people.
In the sample relevant information for two samples are missing. To evaluate skin care
expenditure some essential products are considered that tend to be used more frequently and
almost everybody. The products are cleanser, exfoliate, moisturizer and sunscreen. The different
brands of these items are further categorized as chap, mid range and expensive products. These
are coded as 1, 2 and 3 respectively. For cleanser, number of people using cheap, midrange and
expensive products are 117, 100 and 42 respectively. A total of 259 people are found to use the
product. For exfoliate, number of people using cheap, midrange and expensive products are 68,
67 and 27 respectively. A total of 162 people are found to use exfoliate. In case of moisturizers,
people using cheap brands are numbered 118, while that of midrange and expensive brands are

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81 and 41 respectively. This product has a total of 240 people. The last vital thing is Sunscreen.
Total number of people using Sunscreen is 190. Among them 120 people use cheap brand, 53
use midrange and only 17 people using expensive brand. Therefore, the discussion shows for all
the four products considered people mostly uses cheap brand because of cost advantage.
Maximum number of people uses cleanser and moisturizers followed by sunscreen and exfoliate.
After and age and gender distribution of people the next thing considered is the
distribution of disposable income noted as the spending on skincare product. These are classified
in five separate groups ranging from 0 to 100, 101 to 200, 201 to 300, 301 to 400 and 401 to 500.
Most people belong to the first group that is having expenditure less than 100. The number of
people in this group is recorded as 287. The number of people in second, third and forth groups
followed a descending order.
The first assertion to be tested is whether expenses on skin care vary between male and
female groups. The result shows an acceptance of the hypothesis that there is significant
difference in expense between male and female respondents. Females are likely to spend more
on their skin care product than male does. The analysis reveals support of this assumption.
The next proposition made in the paper is whether opinion between males and females
differ significantly in different aspect. The basic hypothesis here is there is no significant
difference in opinion while the alternate is that there exists significant difference in opinion. The
respondents are asked whether price influence their purchasing decision. In this case the original
hypothesis made is accepted implying the response from female and male are same in this
matter. The next important question is whether they believe expensive skin care products are
better or not. In this case as well no significantly different opinion is found among male and
female responses. Next, the respondents asked whether looking after their skin seems to be

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important for them or not. In this case, the test results shows male and females have different
opinion. There is a statistically significant difference in their responses. The response about
purchasing a skincare product online between males and females can b e said same as no
statistically significant different response is found to be exist in this case.
The age is an important factor that influences spending on skincare. Therefore, statistical
tests are performed to find whether there are any significant differences in spending among
different age groups. The proposition here is no significant difference exists in expenditure
among the age groups with an alternate of existence of significant difference. The test result
shows acceptance of the made proposition in terms of obtained probability value. Therefore, the
discussion suggests age is not an significant influencing factor for skincare expenditure as the
theory suggests.
The fourth and last tested hypothesis is for the difference in expenditure depending on
whether a person suffers from allergy or not. For a person suffering from allergy from a specific
skincare product or others fear of using many products considering their side effects. This limits
spending on many skin care product. The hypothesis tested here is whether any statistically
significant difference in skincare expenditure is found between persons suffering allergies and
those who are not. The result does not show any statistical support for the fact that allergies
significantly influence healthcare expenditure.

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Appendix
Table 1: Proportion of male and female population
Row Labels
Count of
Gender
1 66
2 271
Grand Total 337
Table 2: Age wise distribution of population
Row Labels
Count of
Gender
1 66
2 271
Grand Total 337
Table 3: Frequency table of cleanser brand
Row Labels
Count of
clbrandcode
1 117
2 100
3 42
Grand Total 259
Table 4: Frequency table of exfol brand
Row Labels Count of exfolcode
1 68
2 67
3 27
Grand Total 162

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Table 5: Frequency table of moist brand
Row Labels Count of mobcode
1 118
2 81
3 41
Grand Total 240
Table 6: Frequency table of sunscreen brand
Row Labels Count of suncode
1 120
2 53
3 17
Grand Total 190
Table 7: Distribution of income
Income
Group Frequency
0-100 287
101-200 29
201-300 13
301-400 4
401-500 5
Missing 1
339
Table 8: Correlation between age and number of skin diseases
Age Noiss
Age 1

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Noiss
0.11978593
6 1