英國管理類留學生dissertation范文參考-Simple Data Processing

 

Descriptive analysis is a basic feature for data description, which is mainly used to describe the variables. The analysis can generate descriptive statistics, such as: the mean, variance, standard deviation, range, kurtosis and skewness. Due to these descriptive statistics, we can conduct a comprehensive understanding of the variable characteristics, and compare the degree of variation with different series. The skewness means the skewed direction and degree of the distribution. We need to calculate the coefficient of skewness to measure the degree of deflection. The positive results represent the right skewed distribution. Kurtosis means the acute degree of the top when compared the frequency distribution curve with the normal distribution. When the number equals 3, the distribution curve obey a normal distribution. 

 

We select ‘Analysis →descriptive statistics →description’ command from the editing menu bar, and choose all the variables to get the related descriptive statistics, which is shown as 

描述性分析是對數據的說明中，它主要用于描述變量的基本特征。該分析可以生成描述性統計，如：均值，方差，標準差，范圍，峰度和偏度。由于這些描述性統計，我們可以進行的可變特性的全面了解和比較的變化與不同系列的程度。偏斜裝置的偏斜方向和分布的程度。我們需要計算偏度系數來衡量偏轉的程度。得出積極成果表示右偏態分布。相比與正態分布的頻率分布曲線的峰度是指頂部的尖銳度。當數量等于3，分布曲線服從正態分布。

 

我們選擇“分析→描述統計→說明”從編輯菜單欄中的命令，并選擇所有的變量，以獲得相關的描述性統計，其顯示為

 

Through detailed analysis, It can be found that the data is mostly concentrated. There is no input error. But the distribution does not meet the normal distribution. 

 

Multiple response is a very common form of data in market research. Multiple response data is essentially belong to category data which represent several options to the same problem. We can use the "Multiple Response" command in SPSS to make simple frequency analysis and cross-analyze options through a defined set of variables. However, this analytical method is often not enough; we need to use other analytical methods for depth information. 

 

For the multiple response definition, we should select the menu ‘Analyze → multiple Response → the Define sets’. After we enter into variable settings box, we choose the related variables (options, like ‘VAR5a, VAR5b, VAR5c, VAR5d, VAR5e, and VAR5f’) and put it into the ‘Variables in set’ box. Then we choose the ‘Dichotomies Couted value’ to input 1, and label the set with Keywords (Where hear). At last, we click the ‘Add’ to let it into the ‘Multiple Response sets’ dialog box. All the MCQs can be defined like this process. And the detail information can be used in the next step. （Du & Jia, 2009, p140）#p#分頁標題#e#

 

After the process of the data, we have to analyze the link between different variables by the method of multiple correspondences. Select the ‘Analyze → Dimension Reduction → Optimal Scaling’ from the menu, we can obtain the default settings dialog box. Then we selected variables VAR5a, VAR5b, VAR5c VAR5d VAR5e, and VAR5f as well as nationality age and whether heard. After we define the range of variables, we click OK to obtain the graph. From the graph, we can find out the possible link between the categories of each variable which is located in the same quadrant among the four-quadrant diagram. Specifically, we can see the related contact between variables which is prepared for the depth analysis. 

 

Then we can begin with the frequency analysis and cross-analysis to the data. 

Click the ‘Analyze → multiple Response → Frequencies’ into multiple Response Frequencies dialog box. We put the variable set into the ‘’Table for’ box, and check ‘Exclude cases listwise within dichotomies’ to skip the missing values option. After click OK, we can perform multiple response frequency analysis to display frequency tables, which is shown as Figure 4.2.5. From the Figure, we can see that the exact frequencies. （Du & Jia, 2009, p142）

 

$VAR5 Frequencies

Responses Percent of Cases

N Percent

where heara Local media 45 24.1% 37.8%

China Town Website 24 12.8% 20.2%

Social media 42 22.5% 35.3%

Tourist media 34 18.2% 28.6%

Family and friends 34 18.2% 28.6%

Other 8 4.3% #p#分頁標題#e#6.7%

Total 187 100.0% 157.1%

a. Dichotomy group tabulated at value 1.

 

$VAR8 Frequencies

Responses Percent of Cases

N Percent

impressiona Novel 40 30.3% 51.9%

Happy 39 29.5% 50.6%

Chinese culture 45 34.1% 58.4%

Chaotic 5 3.8% 6.5%

Strange 3 2.3% 3.9%

Total 132 100.0% 171.4%

a. Dichotomy group tabulated at value 1.

 

$VAR10 Frequencies

Responses Percent of Cases

N Percent

favourite parta Performances 36 29.5% 46.2%

Food 28 23.0% 35.9%

Atmosphere 26 21.3% 33.3%

Small goods#p#分頁標題#e# 13 10.7% 16.7%

Cultural display 19 15.6% 24.4%

Total 122 100.0% 156.4%

a. Dichotomy group tabulated at value 1.

 

However, the most important analysis is the statistics from crosstabs. 

Click on ‘Analyze → Multiple Response → Crosstabs’, and enter into ‘Multiple Response Crosstabs’ dialog box. We can click the arrow to move the list of variables into the Rows like nationality, and selected columns variables such as age, then choose the variable response set VAR5 into the layer box. When we define Ranges of the variables, we can click ‘Continue’ button to return to the main dialog box. After that, we need click ‘Options’, and choose all ‘Row, Column, Total’ during the ‘Cell Percentages Check’, then click ‘Continue’ button to return. After we click OK, we can see the implementation process of the Multiple Response Crosstabs analysis. And the detail table will be displayed on Output Viewer board. This is shown as Figure 4.2.6 and Figure 4.2.7. （Du & Jia, 2009, p144）

 (Due to the large quantity of Crosstabs, we have not display all the tables here.)

 

Case Summary

Cases

Valid Missing Total

N Percent N Percent N Percent

VAR1*VAR2*$VAR5 119 100.0% 0 .0% 119 100.0%

 

VAR1*VAR2*$VAR5 Crosstabulation

where heara heard Total

Yes #p#分頁標題#e#No

Local media nationality UK Count 41 41

% within VAR1 100.0%

% within VAR2 91.1%

% of Total 91.1% 91.1%

Other EU Count 1 1

% within VAR1 100.0%

% within VAR2 2.2%

% of Total 2.2% 2.2%

Chinese Count 3 3

% within VAR1 100.0%

% within VAR2 6.7%

% of Total 6.7% 6.7%

Total Count 45 45

% of Total 100.0% 100.0%

China Town Website nationality UK Count 16 16

% within VAR1 #p#分頁標題#e#100.0%

% within VAR2 66.7%

% of Total 66.7% 66.7%

Chinese Count 8 8

% within VAR1 100.0%

% within VAR2 33.3%

% of Total 33.3% 33.3%

Total Count 24 24

% of Total 100.0% 100.0%

Social media nationality UK Count 25 0 25

% within VAR1 100.0% .0%

% within VAR2 61.0% .0%

% of Total 59.5% .0% 59.5%

Other EU Count 3 1 4

% within VAR1 75.0% 25.0%

% within VAR2 #p#分頁標題#e#7.3% 100.0%

% of Total 7.1% 2.4% 9.5%

Chinese Count 12 0 12

% within VAR1 100.0% .0%

% within VAR2 29.3% .0%

% of Total 28.6% .0% 28.6%

Other Count 1 0 1

% within VAR1 100.0% .0%

% within VAR2 2.4% .0%

% of Total 2.4% .0% 2.4%

Total Count 41 1 42

% of Total 97.6% 2.4% 100.0%

Tourist media nationality UK Count 27 #p#分頁標題#e#27

% within VAR1 100.0%

% within VAR2 79.4%

% of Total 79.4% 79.4%

Other EU Count 1 1

% within VAR1 100.0%

% within VAR2 2.9%

% of Total 2.9% 2.9%

Chinese Count 6 6

% within VAR1 100.0%

% within VAR2 17.6%

% of Total 17.6% 17.6%

Total Count 34 34

% of Total 100.0% 100.0%

Family and friends nationality UK Count 16 1 17

% within VAR1 94.1% 5.9%

% within VAR2 48.5% 100.0% #p#分頁標題#e#

% of Total 47.1% 2.9% 50.0%

Chinese Count 17 0 17

% within VAR1 100.0% .0%

% within VAR2 51.5% .0%

% of Total 50.0% .0% 50.0%

Total Count 33 1 34

% of Total 97.1% 2.9% 100.0%

Other nationality Other EU Count 1 0 1

% within VAR1 100.0% .0%

% within VAR2 14.3% .0%

% of Total 12.5% .0% 12.5%

Chinese Count 5 1 6

% within VAR1 #p#分頁標題#e#83.3% 16.7%

% within VAR2 71.4% 100.0%

% of Total 62.5% 12.5% 75.0%

Other Count 1 0 1

% within VAR1 100.0% .0%

% within VAR2 14.3% .0%

% of Total 12.5% .0% 12.5%

Total Count 7 1 8

% of Total 87.5% 12.5% 100.0%

Percentages and totals are based on responses.

a. Dichotomy group tabulated at value 1.

 

According to the Crosstabs analysis of all the questions, we find that there are several variables have relationships.

1, Nationality, Whether heard, and Where heard

2, Nationality, Dragen New Year, and Paticipate

3, Nationality, Paticipate, and Which Performance

4,Nationality, Age, and Impression

5, Paticipate, Time, and Favorite part

6, Nationality, Situation, Think

7, Nationality, Paticipate, Next year

8, Nationality, if negative, Feel

And the depth discussion will surround the relationship and the related ratio.