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Marketing research method – data analysis with SPSS software Research Paper


Executive summary

This is a report on the data analysis carried out in an attempt to understand more about the reasons why people travel to Yarragon village and the kind of activities that they engage in when they are there as well as the experiences that they go through during their stay.

The report is presented through a format where data analysis is carried out and the results presented in a chapter named results of data analysis, then the discussions on the data analysis results are carried out and this is followed by a section the conclusions that the researcher arrived at after carrying out data analysis and finally a section on the recommendations made on the basis of the results of the data analysis is presented.

The data analysis was carried out with the aid of the Statistical Package for Social Sciences (SPSS) and the results are presented though the use of frequency tables.

The analysis involved the determination of the respondents’ profiles through an analysis of the demographic characteristics of the sample such as their age, gender, family composition and the country from which they come from.

This was important in that it helped the researcher to know whether the selected sample was representative of the entire target population.

Other demographic characteristics that were tested were the mode of transport that was used to travel to the village and also the method that the respondents used to get information about the village and its tourist destination.

The respondents were also requested to state the reasons as to why they visited the village and this was intended to answer the research questions about what made people visit the village and what experiences they had while on the visit.

The researcher also wanted to know whether the visitors were travelling in a group all alone and if in a group, the number of people in those groups.

Finally, the researcher carried out a correlation analysis and also tested two hypotheses which were aimed at helping him to answer the overall research questions.

The main results of the study showed that most of the variables tested in the study had a correlation at significant levels of 0.001 and 0.005.

The results also revealed that the hypotheses that were tested were true and these were that the purpose of visit differed across gender and that the intention to return to the village differed across gender.

The study concludes that there are various reasons which influence people to visit the village and these reasons are mostly personal.

The study also concludes that it is important to understand the different attributes of visitors in order to be able to segment them in to groups that can be specifically targeted for particular packages.

The study recommends that it the tourist attractions in the village should ensure that they practice segmentation as well as other forms of marketing in order to ensure continuous flow of visitors to the village.

This research will contribute to the knowledge of tourism management since managers and academicians in this area will be able to understand what factors affect customer’s decision to visit a particular place.

Demographic results

Age of respondents

The researcher sought to know the age of the respondents in the study. The results are presented in the table below

Age group
Frequency Percent Valid Percent Cumulative Percent
Valid 15-24 yrs 20 4.7 4.8 4.8
25-34 yrs 31 7.3 7.4 12.2
35-44 yrs 48 11.2 11.5 23.7
45-54 yrs 76 17.8 18.2 42.0
55-64 yrs 136 31.9 32.6 74.6
65-74 yrs 83 19.4 19.9 94.5
75 yrs or over 23 5.4 5.5 100.0
Total 417 97.7 100.0
Missing System 10 2.3
Total 427 100.0

The results presented above show that a majority (32.6%) of the respondents were between the ages of 55-64 years, 19.9% were between 65-74 years, 18.2% were between 45-54 years, 11.5% between the ages of 35-44 years, 7.3% between the ages of 25-34 years, 5.4% were 75 years and above while another 4.7% were between the ages of 15-24 years.

Gender of respondents

The researcher sought to know the gender of the respondents. The results are presented in the table below.

Gender
Frequency Percent Valid Percent Cumulative Percent
Valid Male 164 38.4 39.7 39.7
Female 249 58.3 60.3 100.0
Total 413 96.7 100.0
Missing System 14 3.3
Total 427 100.0

The results show that a majority (60.3%) of the respondents were female while the other 39.7% were male. This is in line with the census data from the local state which shows that the number of women is much more than the number of women in the population.

Family composition

The researcher sought to know the family composition of the respondents. The results are presented in the table below.

Family composition at home
Frequency Percent Valid Percent Cumulative Percent
Valid Live alone 61 14.3 14.8 14.8
Shared house with no children (e.g. friends) 36 8.4 8.8 23.6
Couple without children at home 211 49.4 51.3 74.9
Couple or single adult with children under 16 years 68 15.9 16.5 91.5
Other 35 8.2 8.5 100.0
Total 411 96.3 100.0
Missing System 16 3.7
Total 427 100.0

The results presented above show that a majority (49.4%) of the respondents were couples without children at home while another 15.9% of the respondents were couples or singles with children who were under the age of 16 years.

Another 14.3% of the respondents lived alone and 8.4% shared houses. This shows that the village attracts the old people more than the middle aged and the young. Measures should be put in place to ensure that all age groups are attracted to the village in order to increase the number of visitors.

Country of origin

The researcher sought to know the country of origin of the respondents. The results are presented in the table below

Country
Frequency Percent Valid Percent Cumulative Percent
Valid Australia 391 91.6 98.5 98.5
New Zealand 2 .5 .5 99.0
Belgium 1 .2 .3 99.2
Holland 1 .2 .3 99.5
England 2 .5 .5 100.0
Total 397 93.0 100.0
Missing System 30 7.0
Total 427 100.0

The results presented above show that a majority (98.5%) of the respondents were from Australia.

This means that most of the visitors to the village are locals and therefore there is need to put up measures to attract more foreign visitors to the village as this will increase the revenue brought to the village and consequently improve the living standards of the locals.

Reason for visiting Yarragon village

The researcher wanted to know the reason why the respondents visit the village. The results are presented in the table below

Reason for visiting Yarragon
Responses Percent of Cases
N Percent
$Question_2a Rest stop 123 18.8% 29.5%
VFR 49 7.5% 11.8%
F&B 208 31.8% 49.9%
Leisure 22 3.4% 5.3%
Shopping 112 17.1% 26.9%
Arts & Galleries 71 10.9% 17.0%
Sightseeing 18 2.8% 4.3%
Sports
Business 17 2.6% 4.1%
Other 34 5.2% 8.2%
Total 654 100.0% 156.8%

The results from the table above reveal that a majority (31.8%) of the respondents visited the village for the consumption of foods and beverages.

Another 18.8% of the respondents visited the village for a rest during trips, 17.1% for shopping purposes, 10.9% to view arts and galleries, 7.5% to visit friends and relatives, 5.2 % for other unspecified reasons, 3.4% for leisure activity, 2.8% for sightseeing and 2.6% for business persons.

This could be attributed to the fact that most of the visitors to the village are local and they therefore visit the village to have meals while in the course of other duties.

It also means that the villagers should increase their investments on tourist attractions in order to increase the number of visitors who come for such purposes.

Frequency of visiting Yarragon

The researcher wanted to know how often the respondents visited Yarragon village. The results are presented in the table below

Frequency of visiting

Frequency Percent Valid Percent Cumulative Percent
Weekly 73 17.1 24.5 24.5
Monthly 118 27.6 39.6 64.1
Once a year 75 17.6 25.2 89.3
Every few years 32 7.5 10.7 100.0
Total 298 69.8 100.0
System 129 30.2
Total 427 100.0

The results presented in the table above show that a majority (39.6%) of the respondents visited the village monthly, 25.2% visited the village once a year, 24.5% visited the village weekly while 10.7% visited the village every few years.

Whether visiting Yarragon Village was primary purpose of visit

The researcher wanted to know whether visiting Yarragon village was the primary purpose of the visit. The results are presented in the table below

Visit YV primary purpose
Frequency Percent Valid Percent Cumulative Percent
Valid Yes 159 37.2 38.5 38.5
No 254 59.5 61.5 100.0
Total 413 96.7 100.0
Missing System 14 3.3
Total 427 100.0

The results show that the visiting the village was the primary purpose of 38.5% of the respondents. The rest 61.5% of the respondents only visited the village as a secondary destination.

This could be due to the fact that most of the visitors to the village are local people and therefore they may decide to visit the village while in the course of other duties.

Form of transportation used

The researcher sought to know the form of transportation used by the respondents. The results are presented in the table below

Transportation used
Frequency Percent Valid Percent Cumulative Percent
Valid Self-drive 396 92.7 93.6 93.6
Commercial bus or coach 1 .2 .2 93.9
Train 9 2.1 2.1 96.0
Other 15 3.5 3.5 99.5
11 2 .5 .5 100.0
Total 423 99.1 100.0
Missing System 4 .9
Total 427 100.0

The results presented above show that a majority 93.6% of the respondents used self drive means of transportation to reach the village. Other means that were used include train services with 2.1% and commercial buses with 0.2%.

Traveling in a travel group

The researcher sought to know whether the respondents travelled in a travel group. The results are presented in the table below

Travel Group
Frequency Percent Valid Percent Cumulative Percent
Valid Alone 99 23.2 23.3 23.3
Spouse or partner 152 35.6 35.8 59.2
Family 106 24.8 25.0 84.2
Friends 66 15.5 15.6 99.8
22 1 .2 .2 100.0
Total 424 99.3 100.0
Missing System 3 .7
Total 427 100.0

The results show that 35.8% of the respondents travelled with their spouses or partner, 25% travelled with family members, 23.3% travelled alone while another 15.6% travelled with their friends.

Expected length of stay

The researcher sought to know the length of stay of the respondents. The results are presented in the table below

Expected length of stay
Frequency Percent Valid Percent Cumulative Percent
Valid Less than 1 hour 189 44.3 45.1 45.1
One to 3 hours 198 46.4 47.3 92.4
3 to 5 hours 17 4.0 4.1 96.4
Overnight 5 1.2 1.2 97.6
Multiple nights 10 2.3 2.4 100.0
Total 419 98.1 100.0
Missing System 8 1.9
Total 427 100.0

The results presented above show that 47.3% of the respondents stayed in the village for a period of between 1-3 hours while another 45.1% stayed in the village for a period of less than 1 hour.

Source of information about village

The researcher sought to know where the respondents got the information about the village from. The results are presented in the table below

Source of information
Responses Percent of Cases
N Percent
$Q13a Nothing 309 78.0% 81.3%
Yarragon brochure/ pamphlet 21 5.3% 5.5%
Visitor Information Centre 6 1.5% 1.6%
Advice from friend or relatives 37 9.3% 9.7%
Yarragon website 2 0.5% 0.5%
Internet search 8 2.0% 2.1%
Facebook
Other 13 3.3% 3.4%
Total 396 100.0% 104.2%

The results show that 78% of the respondents did not seek for information about the village from any source. Another 9.3% of the respondents were advised to visit the village by their friends.

Overall satisfaction

The researcher sought to know the level of satisfaction that the respondents got from visiting the village. The results are presented in the table below

Overall satisfaction
Frequency Percent Valid Percent Cumulative Percent
Valid Very unsatisfied 13 3.0 3.1 3.1
Neither satisfied or unsatisfied 2 .5 .5 3.6
Satisfied 146 34.2 35.2 38.8
Very satisfied 252 59.0 60.7 99.5
7 1 .2 .2 99.8
44 1 .2 .2 100.0
Total 415 97.2 100.0
Missing System 12 2.8
Total 427 100.0

The results show that 60.7% of the respondents were very satisfied with the visit while another 35.2% were satisfied with the visit.

Correlation results

The correlation results show that all the variables correlate at a 0.001 significant level. The researcher also tested two hypotheses, H2: Purpose of visit differs with gender, H3; Intention to return differs with gender. According to the results, the two hypotheses hold.

Conclusions and recommendations

This section presents the conclusions and recommendations of the study based on the results presented above. Conclusions based on the results as well as other relevant literatures are first presented and finally, recommendations are made based on these conclusions.

Conclusions

This study was aimed at testing the reasons why people visited Yarragon villages and the factors that influenced the duration of stay and whether they would make another visit in future.

These conclusions are important since they can be used by the operators of tourism attractions in the village to attract more visitors to the village as well as ensure that visitors make return visits to the village.

Segmentation of visitors

Customer or market segmentation involves a situation where a company divides the market into segments of customers who have common needs or have other common attributes which may influence them to behave in a common way with regards to a particular product.

Segmentation allows a company to design and implement marketing strategies directed at specific groups of people and these strategies are designed on the basis of their needs.

This ensures that the marketing strategies of the company are more effective in terms of attracting more customers as well as maintaining old ones.

Segmentation can be done on the basis of geographical distribution, gender, age, income levels, and country of origin as well as family composition (Kotler & Keller, 2006).

In relation to age, the results of the study showed that (32.6%) of the respondents were aged between 55-64 years, 19.9% aged between 65-74 years, 18.2% between 45-54 years, 11.5% between 35-44 years, 7.3% between 25-34 years, 5.4% were 75 years and above while another 4.7% were between 15-24 years.

This means that the management of the tourist attractions in the village could segment the visitors in terms of age groups and therefore be able to provide the best services for each age group.

This is due to the fact that people of different ages have different tastes and preferences and should therefore be treated differently.

This also means that the management of tourist attractions in the village should develop different packages for the different age groups as they will enjoy different things.

In terms of gender, the results show that a majority (60.3%) of the respondents were female while the other 39.7% were male. This is in line with the census data from the local state which shows that the number of women in the population is much more than the number of women.

It is important to note that gender is a major factor which is used in segmentation due to the fact that people of different gender normally have different perspectives on issues such as tourist destinations and fun activities.

The country of origin is another factor which is commonly used in the segmentation process as people from different countries may have different views on tourist attractions.

The results of the study show that almost all (98.5% the respondents were from Australia. This therefore means that in this case, country of origin cannot be used as a segmentation factor.

Another factor which can be used for segmentation purposes in this case is the respondents’ family composition at home.

This factor is important due to the fact that family composition at home will normally determine the extent to which a visitor will stay in the village and will also determine the amount of money the customer is willing to spend in eh tourist destination.

This is attributed to the fact that if a visitor is a married person, they may opt to stay at the tourist destination for a shorter time than single people. Another dimension is that a visitor with a family may only want to spend a limited amount of money due to other family responsibilities.

Understanding the family composition of the visitors is therefore an important step in ensuring that the tourist destination designs various packages that are suited for all the visitors where specific attractions and packages should be designed to attract people of particular social status.

Marketing

It is important for companies and tourist destinations to develop strategic marketing plans to ensure that they market their products to the customers in a manner that will ensure customers continue increasing and that customers are retained in the company.

In the case of the village, marketing mangers of the different tourist attractions developed various marketing programs and these are based on various characteristics of the visitors being targeted. This targeting can be done based on various attributes of the target customers.

In the case of this study, the marketing managers of such tourist attractions can focus on areas such as the reasons why the visitors normally visit the village.

This would be important in order to be able to understand the various reasons that lead visitors to come to the village and therefore market the village using these reasons.

The results of this study showed that a majority (31.8%) of the respondents visited the village for the consumption of foods and beverages.

Another 18.8% of the respondents visited the village for a rest during trips, 17.1% for shopping purposes, 10.9% to view arts and galleries, 7.5% to visit friends and relatives, 5.2 % for other unspecified reasons, 3.4% for leisure activity, 2.8% for sightseeing and 2.6% for business persons.

Marketing activities have been used in various companies to ensure that customers make increased purchases of their products or makes increased visits to the company.

This can also be possible in the case of the village as the marketing managers can engage in marketing activities in order to ensure that they increase the number of times that the visitors come to visit the village every year.

This will ensure an increase in the earnings that the tourist attractions earn from these visitors (Joshi, 2005).

The results of this study show that a majority (39.6%) of the respondents visited the village monthly, 25.2% visited the village once a year, 24.5% visited the village weekly while 10.7% visited the village every few years.

Marketing initiatives can also be used to ensure that visiting the village becomes the primary purpose of most of the visitors to the area. This will help to ensure that the village tourist attractions receive more visitors every year therefore more revenues.

The results of this study show that the village was the primary purpose of 38.5% of the respondents. The rest 61.5% of the respondents only visited the village as a secondary destination.

This shows that there is need for increased marketing activities to ensure more intended visits to the village. Such initiatives would be expected to convince more visitors to choose the village as their number one tourist destination.

Place as a marketing mix strategy

Marketers also use place as a strategy to ensure that customers purchase their products or use their services. This strategy is used where the product or service is made available for the customers at the right place where it can be reached or accessed with ease.

In the case of this study, place as a strategy can be used through providing transportation means for visitors due to the fact that not all customers are able to afford the cost of taking themselves to the village.

The results of this study show that a majority 93.6% of the respondents used self drive means of transportation to reach the village.

Other means that were used include train services with 2.1% and commercial buses with 0.2%. offering transportation services would also lead to the number of visitors increasing as a result of the perception that it is easy to access the village at a lower cost than when using their own cars.

Recommendations

There are various recommendations that this study made based on the results discussed above. All the recommendations are intended to increase the number of visitors to the village every year and at the same time increase the length of stay and frequency of visits by customers.

The management of the tourist attractions in the village should ensure that they develop segmentation strategies which will be aimed at identifying the various segments of the visitors and their specific needs.

This will ensure that the tourist attractions develop various packages in an attempt to target and attract particular groups of people.

This strategy will ensure that visitors are satisfied with what they are offered and therefore make return trips to the village and at the same time, influence their friends and relatives to visit the village and experience the good packages offered.

It is also important for the management of these tourist attractions to engage in more marketing activities in order to ensure that the village receives more visitors and also to ensure that a lot of potential visitors are made aware of the tourist attractions that the village offers in an effective way.

This research will contribute to the knowledge of tourism management since managers and academicians in this area will be able to understand what factors affect customer’s decision to visit a particular place.

References

Joshi, R.M. (2005). International Marketing. Oxford University Press: New Delhi.

Kotler, P. & Keller, K.L. (2006). Marketing Management. Prentice Hall: London.

Appendices

Hypothesis results

Independent Samples Test
Levene’s Test for Equality of Variances t-test for Equality of Means
F Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference
Lower Upper
Visit YV primary purpose Equal variances assumed 4.896 .027 1.081 398 .281 .054 .050 -.044 .152
Equal variances not assumed 1.086 351.614 .278 .054 .049 -.044 .151
Intend to return to YV Equal variances assumed .517 .472 -.351 394 .726 -.020 .056 -.129 .090
Equal variances not assumed -.413 329.352 .680 -.020 .047 -.113 .074

Correlation results

Correlations
Residence Postcode Country First Visit F&B How often visit Where trip started (home if same as Q1) Location of trip start Where trip finished (home if same as Q1) Location of trip finish Visit YV primary purpose Transportation used Travel Group Number in travel group Number less than 16yo Expected length of stay Intend to return to YV Spending – Retail Spending – Accommodation Spending – Food and Beverage Overall satisfaction Age group Gender Family composition at home
Residence Pearson Correlation 1
Sig. (2-tailed)
N 413
Postcode Pearson Correlation 0.005 1
Sig. (2-tailed) 0.922
N 409 418
Country Pearson Correlation 0.007 -.300** 1
Sig. (2-tailed) 0.895 0
N 384 390 397
First Visit Pearson Correlation -.107* 0.016 -.243** 1
Sig. (2-tailed) 0.031 0.748 0
N 406 411 391 419
F&B Pearson Correlation -0.079 -0.05 -0.012 0.026 1
Sig. (2-tailed) 0.264 0.47 0.873 0.714
N 202 207 194 206 210
How often visit Pearson Correlation .185** -.321** .163** -0.07 -0.068 1
Sig. (2-tailed) 0.002 0 0.007 0.232 0.414
N 290 293 276 295 147 298
Where trip started (home if same as Q1) Pearson Correlation .151** -0.031 .116* -.195** -0.05 .210** 1
Sig. (2-tailed) 0.002 0.533 0.022 0 0.467 0
N 411 415 394 416 210 297 423
Location of trip start Pearson Correlation .725** -0.063 -0.063 0.048 -0.069 .159** 0 1
Sig. (2-tailed) 0 0.2 0.214 0.334 0.318 0.006 0.99
N 410 413 391 413 209 295 420 420
Where trip finished (home if same as Q1) Pearson Correlation .194** -.157** .149** -.158** 0.038 .224** 0.05 0.09 1
Sig. (2-tailed) 0 0.001 0.003 0.001 0.587 0 0.34 0.08
N 412 415 394 416 209 297 422 419 423
Location of trip finish Pearson Correlation .571** -0.024 -0.067 -0.079 -0.052 0.1 0.07 .515** -0.026 1
Sig. (2-tailed) 0 0.622 0.189 0.108 0.452 0.087 0.14 0 0.593
N 409 411 390 412 208 296 418 417 419 419
Visit YV primary purpose Pearson Correlation .181** -.104* -0.087 -0.039 -0.013 .262** .210** .174** .385** .160** 1
Sig. (2-tailed) 0 0.036 0.088 0.429 0.856 0 0 0 0 0.001
N 401 405 385 408 204 292 411 408 411 407 413
Transportation used Pearson Correlation -0.057 0.09 -0.023 0.022 -0.022 -0.084 -0.07 -0.06 -.106* -0.045 -.192** 1
Sig. (2-tailed) 0.246 0.066 0.653 0.656 0.75 0.149 0.13 0.22 0.03 0.362 0
N 410 415 394 416 210 297 420 417 420 416 411 423
Travel Group Pearson Correlation 0.01 0.013 0.064 -0.064 -0.084 0.064 0.01 0 0.009 0.018 -0.038 .343** 1
Sig. (2-tailed) 0.833 0.79 0.201 0.195 0.228 0.274 0.81 0.95 0.852 0.72 0.439 0
N 411 416 395 417 209 296 421 418 421 417 411 421 424
Number in travel group Pearson Correlation 0.093 -0.014 0.013 -0.053 -0.122 .155** 0.07 0.07 0.005 0.047 -0.013 -0.033 .405** 1
Sig. (2-tailed) 0.063 0.782 0.804 0.28 0.08 0.008 0.15 0.15 0.915 0.345 0.793 0.503 0
N 405 410 390 411 208 294 415 412 415 411 406 417 417 418
Number less than 16yo Pearson Correlation -0.144 -0.153 .b -0.215 .b -0.229 0.15 -0.2 -0.065 -0.117 -0.167 0.214 -0.3 .413** 1
Sig. (2-tailed) 0.345 0.317 0 0.16 0 0.208 0.34 0.18 0.669 0.448 0.296 0.159 0.07 0.01
N 45 45 43 44 23 32 45 45 45 44 41 45 45 43 45
Expected length of stay Pearson Correlation -.111* -0.027 .134** -0.077 0.049 -0.008 -.111* -.098* -0.058 -.163** -.354** 0.072 -0 0.02 -0.16 1
Sig. (2-tailed) 0.025 0.585 0.008 0.118 0.481 0.894 0.02 0.05 0.237 0.001 0 0.142 0.6 0.72 0.314
N 406 411 391 413 207 295 416 413 416 412 408 418 417 413 44 419
Intend to return to YV Pearson Correlation 0.038 -0.032 0.055 -0.098 -0.017 0.003 0.07 0.01 .108* 0.01 0.072 -0.008 -0 -0.03 0.128 -0.07 1
Sig. (2-tailed) 0.449 0.522 0.285 0.05 0.814 0.961 0.15 0.83 0.03 0.837 0.154 0.868 0.65 0.6 0.415 0.166
N 394 400 379 400 202 291 404 402 403 399 395 405 404 401 43 403 406
Spending – Retail Pearson Correlation 0.086 0.08 0.015 0.032 -0.107 0.063 -0.04 0.09 -0.011 0.123 -0.049 0.1 -0.1 -0.04 -0.11 0.036 -0 1
Sig. (2-tailed) 0.256 0.289 0.845 0.666 0.327 0.477 0.6 0.26 0.884 0.103 0.521 0.182 0.13 0.56 0.698 0.629 0.7
N 176 178 167 179 86 130 179 178 179 178 175 179 179 179 15 179 176 180
Spending – Accommodation Pearson Correlation -0.214 0.042 .b -0.138 .b .b -0.07 -.730* -0.332 0.094 -0.332 .b 0.31 0.53 .b -0 .b 0.67 1
Sig. (2-tailed) 0.579 0.921 0 0.724 . 0 0.87 0.04 0.382 0.811 0.382 0 0.41 0.14 . 0.991 0 0.15
N 9 8 8 9 0 3 8 8 9 9 9 9 9 9 0 9 7 6 9
Spending – Food and Beverage Pearson Correlation 0.04 0.045 -0.02 -.155** -0.083 0.053 -0.05 0.04 -0.03 -0.076 -0.078 .158** -0 0.11 -0.06 .434** -0 0.16 0.641 1
Sig. (2-tailed) 0.492 0.434 0.742 0.007 0.282 0.436 0.41 0.5 0.605 0.189 0.182 0.006 0.94 0.05 0.707 0 0.6 0.1 0.087
N 298 302 288 302 170 221 305 303 305 301 298 306 306 305 37 303 293 114 8 307
Overall satisfaction Pearson Correlation -0.007 0.013 -0.04 0.067 -0.005 -0.051 -0.05 0.01 0.03 0.005 -0.011 0.094 0.01 0 .304* .185** -0 0.09 -0.129 -0.03 1
Sig. (2-tailed) 0.893 0.795 0.435 0.175 0.945 0.384 0.27 0.87 0.55 0.92 0.82 0.056 0.92 0.99 0.042 0 0.9 0.24 0.742 0.604
N 402 408 388 408 205 293 412 409 412 408 403 413 413 408 45 410 398 179 9 305 415
Age group Pearson Correlation -0.02 0.003 0.071 0.058 -0.001 -0.055 -0.04 -0.04 -0.006 0.005 -0.063 -0.004 -0 -0.02 0.291 -0.04 0 -0.03 0.072 -0 -0.073 1
Sig. (2-tailed) 0.694 0.958 0.164 0.242 0.989 0.349 0.45 0.42 0.905 0.918 0.205 0.939 0.61 0.67 0.052 0.472 1 0.74 0.854 0.979 0.139
N 404 410 390 410 206 293 414 411 414 410 404 414 415 409 45 411 398 180 9 305 413 417
Gender Pearson Correlation -0.027 0.086 -0.046 0.049 0.084 0.062 -0.04 -0 -0.048 -0.053 -0.054 -0.045 0.01 0.07 -.315* 0.008 0 0.02 0.572 -0.03 0.035 -.166** 1
Sig. (2-tailed) 0.593 0.085 0.363 0.325 0.235 0.296 0.47 0.93 0.336 0.288 0.281 0.361 0.81 0.14 0.037 0.877 0.7 0.82 0.138 0.652 0.49 0.001
N 400 406 385 406 201 290 410 407 410 406 400 410 411 406 44 406 396 176 8 299 403 406 413
Family composition at home Pearson Correlation 0.047 -0.051 -.167** 0.016 0.056 0.023 0.03 0.09 -0.084 0.026 -0.047 -0.004 0.06 .116* -0.28 0.059 0 0.03 0.086 0.09 0.079 -.284** .168** 1
Sig. (2-tailed) 0.352 0.305 0.001 0.754 0.429 0.698 0.6 0.08 0.091 0.604 0.348 0.941 0.25 0.02 0.068 0.235 0.9 0.71 0.825 0.12 0.109 0 0.001
N 399 404 384 404 201 288 409 406 409 405 399 408 409 403 44 405 392 177 9 301 407 410 400 411
* Correlation is significant at the 0.05 level (2-tailed).
** Correlation is significant at the 0.01 level (2-tailed).
b Cannot be computed because at least one of the variables is constant.

This Research Paper on Marketing research method – data analysis with SPSS software was written and submitted by user Carlos Munoz to help you with your own studies. You are free to use it for research and reference purposes in order to write your own paper; however, you must cite it accordingly.

Carlos Munoz studied at American University, USA, with average GPA 3.14 out of 4.0.

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Munoz, C. (2019, July 4). Marketing research method - data analysis with SPSS software [Blog post]. Retrieved from https://ivypanda.com/essays/marketing-research-method-data-analysis-with-spss-software/

Work Cited

Munoz, Carlos. "Marketing research method - data analysis with SPSS software." IvyPanda, 4 July 2019, ivypanda.com/essays/marketing-research-method-data-analysis-with-spss-software/.

1. Carlos Munoz. "Marketing research method - data analysis with SPSS software." IvyPanda (blog), July 4, 2019. https://ivypanda.com/essays/marketing-research-method-data-analysis-with-spss-software/.


Bibliography


Munoz, Carlos. "Marketing research method - data analysis with SPSS software." IvyPanda (blog), July 4, 2019. https://ivypanda.com/essays/marketing-research-method-data-analysis-with-spss-software/.

References

Munoz, Carlos. 2019. "Marketing research method - data analysis with SPSS software." IvyPanda (blog), July 4, 2019. https://ivypanda.com/essays/marketing-research-method-data-analysis-with-spss-software/.

References

Munoz, C. (2019) 'Marketing research method - data analysis with SPSS software'. IvyPanda, 4 July.

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