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Report on Introduction to Statistics and Questionnaire Design

   

Added on  2020-04-15

4 Pages1468 Words51 Views
Data Science and Big DataStatistics and Probability
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Introduction to statistics and questionnaire design: Statistical methods basically a process of collection, summarizing, analysis and theinterpretation of the analysis. (Bethlehem, 2009)Making questionnaire on the basis of the importance of factors of the study of theorganization. The characteristics of the study will contain, a specific plan, designstructure to get the answers from the respondents.The questionnaire will contain thequestions related to the open ended, closed ended, and the nominal, ordinal and intervallevel ratio variables. The analysis of the collected data from the questionnaire willindicate the strength, weakness, opportunities and threats of the factors of the study. Thestatistical data will indicate a summary statistics of the analysis, which will contain thegraphical representation of each factor, numerical summary of each factor and the finalprincipal components of the study. (Brace, 2008).The procedure of the analysis can be derived as follows: a. Topic selection: - Scale should not be wide are level of measurement should beaccurate. b. Determination of hypothesis: - it includes the objective of the study. c. Sampling method: - Selecting an appropriate sampling method related to the study. d. Data collection: - Data should be collected through direct interview or by other similarcompanies’ data. e. Data handling: - Coding and putting the responses in to level of measurements. f. Statistical Analysis: -It includes the appropriate statistical model for the analysis. i. Gathering of results: - It includes the graphical and numerical representation of thedata. j. Conclusions: - Determine the findings related to the hypothesis of the study. (Heeringa,West and Berglund, 2010)Data types: There are two types of data which can be used for analysis, first is Primary data, whichcan directly collected from the customers of the organization on the basis ofquestionnaire. And other is Secondarydata, which can collected from official website ofthe organization and also from other official websites related to organization. (Bordens,Abbott, 2013)Statistical methods and modeling: Statistical methods basically a process of collection, summarizing, analysis and theinterpretation of the analysis. Data collection is a process of collection of data related tothe information required in the questionnaire. In this process, the sampling processinvolved and required to calculate the representative sample size of the population. Thusa sample is a representative of the population will indicates the unbiased results of thestudy, also the method of data collection will unbiased. Data summarization is a processof calculating appropriate statistics of the data, and summarizing the data by usinggraphs, tables and charts. Thus, a researcher can visualize the results on the basis ofgraphical representation of the factors of the study and can summarize the results on thebasis of summary statistics. (Reid, 2013).Analysis of data contains an appropriate method for the study, we can use differentstatistical methods for a data on the basis of the purpose of the study. Consider themultiple regression model for factor analysis and the future prediction: 1 12 23 3iiiiim mi iX A F A F A FA F VUWhereXi = ith standardized variableAij = standardized multiple regression coefficient of variable I on common factor jF= common factorVi = standardized regression coefficient of variable I on unique factor IUi = the unique factor for variable im = number of common factorsThe model for the common factors which are uncorrelated can be defined as the linearcombination:Fi = Wi1x1 + Wi2X2 + Wi3X3 + ... + WikXkWhere,Fi = estimate of i th factorWi = weight or factor score coefficientk = number of variables.
Report on Introduction to Statistics and Questionnaire Design_1

The steps of directing factor analysis are as below:Problem formulation.↓Obtain the correlation matrix.↓Find the appropriate model of factor analysis.↓Compute the number of factors.↓Rotate the factors.↓Interpret the factors Variables↓Calculate the Select theFactor scores Surrogate.↓Determine the model fitThus, by using factor analysis, a researcher can predict the factors which shows thestrength, weakness, opportunities and threats of the study. The strength will indicate theeffective factors, the weakness will indicate the weak factors of the study, theopportunities will indicate that which factors have to improve and the direction of theimprovement, threats will indicates the causes which can trouble in the future. (Brown,2015)Interpretation of the analysis will indicate the areas where the organization have toimprove, and which intimidations can trouble the organization. By, using the analysis anorganization can improve market strategy and can make future plans related to thefactors. (Pahl and Richter, 2009)Deductive and inductive approaches:The deductive approach is basically related to making the hypothesis on the basis oftheoretical information and making the research strategy. The inductive approach isbasically based on the observational study based on the research process. Thus, aresearcher can use the deductive and inductive approaches on the basis of the research.Thus, both approaches can be used in business intelligence which will depend on thehypothetical/ Observational study. (Wilson, 2010) Analysis of the samples: Consider the data of sales of coffee from year 2005 to 2009, to predict the sales of coffeein the quarter 20 of the year 2010, we can use regression analysis. The regression modelfor the analysis of data is given below:Sales of coffeeQuarterNow use the Excel to run the regression analysis, the obtained regression analysis isgiven as below: SUMMARY OUTPUTRegression StatisticsMultiple R0.5602852R Square0.3139195Adjusted R Square0.2758039Standard Error13.154284Observations20ANOVAdfSSMSFSignificanceFRegression11425.11611425.1168.23590.0101870Residual183114.6338173.0352Total194539.75CoefficientsStandard Errort StatP-valueLower 95%Intercept21.8786.11053.5800.002139.04109695Quarter1.463900.51012.86980.010180.39222672According to above results, the prediction equation for the sales of coffee is given as:
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