AMB201 Marketing & Audience Research
Quantitative Project Analysis Document
The following pages describe the way the AMB201 data were cleaned and coded, the various analyses
used, and the results obtained (using SPSS). The analysis has been done for you – you can simply
write up results from in this document. Alternatively, the dataset and the syntax used to analyse the data
are provided on Canvas only if you would like to conduct your own analysis for practice (there is no
requirement that you need to conduct your own analysis). This document should be used in
conjunction with other material/instruction delivered as part of the unit. Please note that the analyses and
explanations presented here have been simplified for the purposes of AMB201.
For the analysis section of your report you will need to address the following:
 Data cleaning and editing
o A few sentences outlining how the data were cleaned and edited to allow for analysis.
 Descriptives
o Provision of descriptive statistics to ensure the reader has an idea of the nature of the
dataset (e.g., sample size, group sizes, construct means, etc.).
 Analysis for Objective 1
o To examine if attitudes toward plant-based meat differ across population segments.
o Choose two segmentation variables of five we measured (age cohort, gender, relationship
status, Preferred place to eat plant-based meat, frequent plant-based meat eater);
o Report the results of two t-tests considering potential differences in attitudes toward
plant-based meat across your chosen segments.
 Analysis for Objective 2
o To understand the relationships between individual characteristics and attitudes
toward plant-based meat;
o Choose two individual characteristics constructs of the five we measured (consumer
innovativeness, impulsiveness, price consciousness, health concern, and
environmentalism);
o Report the results of the correlation analysis between attitudes toward plant-based
meat and each of your two chosen individual characteristics.
 Analysis for Objective 3
o To evaluate the relationship between attitudes toward plant-based meat and (1) attitudes toward
convenience food; (2) attitudes towards single-serve packaged product;
o Consider both of attitudes we measured (attitudes toward convenience food, attitudes
toward single-serve packaged product);
o Report the results of the correlation analysis between attitudes toward plant-based
meat and each of the two attitudes (towards convenience food, towards single-
serve packaged product).
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Data cleaning and editing
Data cleaning procedure (already done for you)
Issues identified with items where respondents could freely enter data and corrections made:
 Deleted respondents with uninterpretable or nonsense responses (e.g., PostCode = “20”, Nationality =
“1”)
 Converted birth year to age in years (e.g., “1995”  28)
Frequencies were run to check values were all in range.
 All values within range (e.g., check for values entered outside of 1-7 range for 1-7 scales; 1-10 range for 1-
10 scales)
 All ages within range? (i.e., check no-one under 18 years, if so exclude)
 Respondents allocated to correct generational cohort (check age and name those whose age is equal or below
40 as younger cohort and those whose age is above 40 as older cohort)
 Respondents allocated to frequent plant-based meat eater cohort (check frequency of eating plant-based
meat and name those whose responses are 1~4 (always ~ occasionally) as frequent eater and those whose
responses are 5~6 (seldom ~ Never) as infrequent eater)
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Reverse coding (already done for you)
SPSS was used to reverse responses to negatively phrased survey items. All negatively phrased items are
shown in the Variable Codes document and Codebook on Canvas. For example, CI3 was reversed such
that responses of 1 were recoded as 7, responses of 2 were recoded as 6, etc. Reversed items are listed
below and variable names are appended with “_R” in the dataset:
 CI3  CI3_R
 CI4  CI4_R
 CI7  CI7_R
 IMP3  IMP3_R
 IMP4  IMP4_R
Construct calculations (already done for you)
Construct values were determined for each respondent by averaging across the relevant items.
 ATTA = (ATTA1 + ATTA2 + ATTA3 + ATTA4 + ATTA5 + ATTA6 + ATTA7 + ATTA8 +
ATTA9)/9
 ATTBI= (ATTBI1 + ATTBI2 + ATTBI3)/3
 CI = (CI1 + CI2 + CI3_R + CI4_R + CI5 + CI6 + CI7_R)/7
 IMP = (IMP1 + IMP2 + IMP3_R + IMP4_R)/4
 PC = (PC1 + PC2 + PC3 + PC4)/4
 HC = (HC1 + HC2 + HC3 + HC4)/4
 ENV = (ENV1 + ENV2 + ENV3 + ENV4)/4
 ACF = (ACF1 + ACF2 + ACF3 + ACF4 + ACF5 + ACF6 + ACF7 + ACF8 + ACF9)/9
 ASPP = (ASPP1 + ASPP2 + ASPP3 + ASPP4 + ASPP5 + ASPP6 + ASPP7 + ASPP8 + ASPP9)/9
Dependent Variable decision
Two dimensions of attitude were measured: Affective (ATTA) and Behavioural Intention (ATTBI). For
simplicity, only the affective dimension of attitude (ATTA) will be analysed as the dependent variable
for the AMB201 report.
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Descriptives: Descriptive Statistics
The following table shows the overall mean (and standard deviation) for each construct relevant to our
analysis, as well as the minimum and maximum scores given by respondents in the dataset.
Descriptive Statistics
N Minimum Maximum Mean
Std.
Deviation
ATTA 529 1.00 7.00 4.2132 1.51786
CI 529 1.00 7.00 4.5428 .94860
IMP 529 1.00 7.00 4.2046 1.32799
PC 529 1.00 7.00 5.1129 1.14135
HC 529 2.50 7.00 5.5888 1.03428
ENV 529 1.00 7.00 5.0336 1.24390
ACF 529 1.00 10.00 6.0542 1.97501
ASPP 529 1.00 10.00 5.3915 2.02915
Valid N
(listwise)
529
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Descriptives: Frequencies
Frequencies show the counts and percentages of respondents across categories. These can be used to
determine the proportion of people falling into each group.
Gender
Frequency Percent
Valid
Percent
Cumulative
Percent
Valid Man 259 49.0 49.0 49.0
Woman 266 50.3 50.3 99.2
Other 2 .4 .4 99.6
Prefer not to
say
2 .4 .4 100.0
Total 529 100.0 100.0
Age Cohort
Frequency Percent
Valid
Percent
Cumulative
Percent
Valid Younger 18-
40
297 56.1 56.1 56.1
Older 40+ 232 43.9 43.9 100.0
Total 529 100.0 100.0
Relationship
Frequency Percent
Valid
Percent
Cumulative
Percent
Valid Single 195 36.9 36.9 36.9
Partnered 334 63.1 63.1 100.0
Total 529 100.0 100.0
Place to eat PBM
Frequency Percent
Valid
Percent
Cumulative
Percent
Valid At home 250 47.3 47.3 47.3
In a
restaurant
220 41.6 41.6 88.8
Other 59 11.2 11.2 100.0
Total 529 100.0 100.0
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Frequent PBM Eater
Frequency Percent
Valid
Percent
Cumulative
Percent
Valid Yes: Always ~
Occasionally
241 45.6 45.6 45.6
No: Seldom or Never 288 54.4 54.4 100.0
Total 529 100.0 100.0
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Descriptives: Crosstabulations
Crosstabs are a common way of depicting descriptive results in marketing research because of their
simplicity. They show one group (e.g., gender) crossed with another group (e.g., age cohort).
Gender * Age Cohort Crosstabulation
Count
Age Cohort
Total
Younger 18-
40
Older
40+
Gender Man 149 110 259
Woman 144 122 266
Other 2 0 2
Prefer not to
say
2 0 2
Total 297 232 529
Relationship * Age Cohort Crosstabulation
Count
Age Cohort
Total
Younger 18-
40
Older
40+
Relationship Single 162 33 195
Partnered 135 199 334
Total 297 232 529
Place to eat PBM * Age Cohort Crosstabulation
Count
Age Cohort
Total
Younger 18-
40
Older
40+
Place to eat
PBM
At home 138 112 250
In a
restaurant
130 90 220
Other 29 30 59
Total 297 232 529
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Frequent PBM Eater * Age Cohort Crosstabulation
Count
Age Cohort
Total
Younger 18-
40
Older
40+
Frequent PBM
Eater
Yes: Always ~
Occasionally
143 98 241
No: Seldom or Never 154 134 288
Total 297 232 529
Frequent PBM Eater * Gender Crosstabulation
Count
Gender
Total Man Woman Other
Prefer not to
say
Frequent PBM
Eater
Yes: Always ~
Occasionally
95 143 2 1 241
No: Seldom or Never 164 123 0 1 288
Total 259 266 2 2 529
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Descriptives: Other
The graph below shows spread of respondents’ ages and frequency of eating plant-based meat. You might
like to consider any notable features of this distribution and possible implications that could be relevant
for your report.
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Analysing the constructs relevant to the AMB201 objectives
Objective 1:
To examine if attitudes toward plant-based meat differ across population segments.
Analysis using t-tests
To address this objective, t-tests can be conducted. A t-test is used to compare two groups to answer
questions such as does attitude toward plant-based meat differ between male and female? SPSS output
appears below.
Does attitude toward plant-based meat differ between male and female?
Group Statistics
Gender N Mean
Std.
Deviation
Std. Error
Mean
ATTA Man 259 3.95 1.57668 .09797
Woman 266 4.47 1.41139 .08654
In this first table (above) the descriptive statistics for the two groups are shown. It can be seen that the
mean attitude rating for the female group (Mean = 4.47) looks a bit higher than the mean attitude rating
for the male group (Mean = 3.95). Despite this apparent difference, it is important to check if these means
are statistically different. This is done by looking at the t-test statistics.
The table above shows the results of a t-test (for your assignment, it is okay to just use the first row,
corresponding to “Equal variances assumed”). The Significance (Two-sided p) value (i.e., <.001) is less
than 0.05, so it can be concluded that there is statistically significant difference between the two groups.
That is, the mean attitude rating reported by the female group is higher as the mean attitude reported by
the male group.
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Look at the t-test example below to see results for when two means are not significantly different – that
is, where the Significance. (Two-sided) value is not less than 0.05. In cases like this it can be concluded
that there is not a statistically significant difference between the two groups, regardless of how the
means look.
Does attitude toward plant-based meat differ between younger and older people?
Group Statistics
Age Cohort N Mean
Std.
Deviation
Std. Error
Mean
ATTA Younger 18-
40
297 4.30 1.48999 .08646
Older 40+ 232 4.10 1.54868 .10168
See additional t-test results for other comparisons on the next page.
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Other examples…
Does attitude toward plant-based meat differ between single and partnered people?
Group Statistics
Relationship N Mean
Std.
Deviation
Std. Error
Mean
ATTA Single 195 4.42 1.39677 .10002
Partnered 334 4.09 1.57330 .08609
Does attitude toward plant-based meat differ between the preferred place to eat plant-based meat?
Group Statistics
Preferred Place
to eat PBM N Mean
Std.
Deviation
Std. Error
Mean
ATTA At home 250 4.57 1.43743 .09091
In a restaurant 220 4.13 1.45231 .09791
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Does attitude toward plant-based meat differ between frequent plant-based meat eaters and infrequent plant-
based meat eaters?
Group Statistics
Frequent PBM Eater N Mean
Std.
Deviation
Std. Error
Mean
ATTA Yes: Always ~
Occasionally
241 5.22 .98228 .06327
No: Seldom or Never 288 3.37 1.36587 .08048
For your report: Choose two segmentation variables of the five we measured (age cohort, gender,
relationship status, Preferred place to eat Plant-based meat, frequent plant-based meat eater), and outline
the results of the two corresponding t-tests. For each segmentation variable you should report the means
for the groups being compared, the t value, and the significance level. It can also be useful to include a
brief statement describing the results in everyday language. Save discussing implications until the
discussion section of the report.
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Analysing the constructs relevant to the AMB201 objectives
Objective 2:
To understand the relationships between individual characteristics and attitudes toward plant-based meat
Analysis using correlation
To address this objective, we use correlation analysis. Correlations provide a measure of the relationship
between two variables. When reporting correlation, it is useful to describe the size/strength of correlation,
the direction of the correlation (+/-), and whether it is significant (shown with * or ** in the table).
Correlation
ATTA
ATTA Pearson Correlation 1
Sig. (2-tailed)
N 529
CI Pearson Correlation .249**
Sig. (2-tailed) <.001
N 529
IMP Pearson Correlation .097*
Sig. (2-tailed) .025
N 529
PC Pearson Correlation .027
Sig. (2-tailed) .535
N 529
HC Pearson Correlation .200**
Sig. (2-tailed) <.001
N 529
ENV Pearson Correlation .408**
Sig. (2-tailed) <.001
N 529
Correlation is significant at the 0.01 level (2-tailed).**
Correlation is significant at the 0.05 level (2-tailed).*
For your report: Choose two individual characteristics constructs and consider the relevant correlation
analysis results. As well as reporting the statistical results, it can be useful to include a brief statement
describing what the results mean in everyday language. Save discussing any implications until the
discussion section of the report.
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Analysing the constructs relevant to the AMB201 objectives
Objective 3:
To evaluate the relationship between attitudes toward plant-based meat and (1) attitudes toward
convenience food; (2) attitudes towards single-serve packaged product.
Analysis using correlation
To address this objective, we use correlation analysis. You should report correlations for this objective in
a similar manner to that described for the previous objective. That is, describe the size/strength of the
correlation, the direction of the correlation (+/-), and whether it is significant (shown with * or ** in the
table if there is any).
ATTA
ATTA Pearson Correlation 1
Sig. (2-tailed)
N 529
ACF Pearson Correlation -.008
Sig. (2-tailed) .857
N 529
ASPP Pearson Correlation .053
Sig. (2-tailed) .227
N 529
For your report: Consider the relevant correlation analysis results for the two key relationships (i.e., the
correlation between attitudes toward plant-based meat & attitudes toward convenience food, and the
correlation between attitudes toward plant-based meat & attitudes toward single-serve packaged
product). As well as reporting the statistical results, it can be useful to include a brief statement describing
what the results mean in everyday language. Save discussing any implications until the discussion section
of the report.