Hey Arman, Your study sounds to be having some similarities with our Research. Our Research Findings can be found here, including in-depth Statistical Analysis we used. Comment/ Recommend if you got some idea from our study. Good luck!

Experiment Findings FACTOR ANALYSIS ON SALES PERFORMANCE OF ENTREPRENEURS IN NOR...

Your research involves ordinal variables since they are based on likert-scaled answers. Analysis must be on the basis of nonparametric statistical tests like Wilcoxon signed rank test, Mann Withney U test, Kruskal Wallis test, Spearman's rank correlation test , etc.

You should have the basic knowledge on statistical analysis before developing any proposal. It will help you to give a better shape of your questionnaire too. You have to use descriptive as well as analytical statistics. You have a total score after all the opinions then you can do many things to identify your predictors too.

You can follow at least one good statistical book for this.

Maybe the simplest and most valid - coefficient of coincidence - C.o.c.

It would be useful to use SPSS and Pearson Correlation Coefficient.

You can investigate the possibility of forming a scale from your Likert-scored variables. If you can create a scale with adequate reliability and validity, then you could use it as an interval-level dependent variable in analyses such as t-Tests, Analysis of Variance, and regression.

For me, ideally SPSS. but, Excel could help too, depending on the number of cases (valid responses) to each of your questions. Excel has an stat functions (fx) and Add ins that can help you process the data, or, you can process it on SPSS and later move the data to Excel to shape it on graphs, unless you have access to the new SPSS which has a lovely suit for reporting.

You may or may not build an index based on the Likert Scale, it will depend on the logical and content relation between the statements of the scales. BUt you could do a demo mapping: contrasting each scale to demographic factors of your sample.

Pearson would be helpful too.

I will recommend you to follow David Morgan's advice.

Apparently, you're using multiple items to measure attitude towards using Halal products. The best way would be compute a scale variable, after checking reliability and validity. The scale variable can be computed by taking mean score or sum score.

Buenas noches deberias iniciar usando la estadística descriptiva, si estas buscando vinculación entre las variables puedes usar la estadística inferencial según el tipo de variables

U have to check reliability and validity of the questionnaire.

Use all of your Likert questions to establish one or more scale scores. Check the reliability and validity of your scale scores. Do you plan to compare Non-Muslims to some other group or groups? If this were the case, you could use a t-test to compare two groups or ANOVA to compare multiple groups on your various scale scores. Before doing all of this, I'd run Factor Analysis on all of your Likert items. The Factor Analysis will help you determine the number of scales you should be using with your data.

Do a pilot study by framing a questionnaire meeting ur objective of your study Take the opinion of marketing expert in that particular product line

check for normality test and if it is abnormal data

then to test two variables go for t test if there is more than two variables to test go for anova and coefficient of determination tells the strength of relationship between variables

To analyze Likert scale data, including a Chi Square statistic, compare actual responses with expected responses.

The Chi Square evaluates the statistical significance of a given hypothesis. The greater the level of deviation between the actual and expected responses, the higher the chi-square statistic will be and, therefore, the results will be less fit to the hypothesis.

Valuable inputs from RG fellows.

First you have to quantify your hypothesis that non-muslims in Germany refuse to buy halal products because______ percent of Non- Muslims would not buy products that are Halal. I guess the hypothesis is quite sweeping. Perhaps hypothesis could be revised to: a significant number of Non- Muslims in Germany refuse to buy halal products. one can use categorical data anslysis both nominal and ordinal.

Normality test (deciding to use parametric / non-parametric statistics), descriptive statistics, reliability test (Cronbach Alpha / Composite Reliability), Pearson / Spearman correlational test