Multiple regression analysis was performed on profitability of deposit taking

Multiple regression analysis was performed on

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Multiple regression analysis was performed on profitability of deposit taking SACCOs as the dependent variable whereas Loan performance management, fixed assets management, financial investments management and accounts receivable management were the independent variables in the model. Analysis of variance (ANOVA) was also be used to test the significance of the model in explaining the relationship between variables. The formulated research hypotheses was tested using regression analysis at 5% significance level. The following model was adopted to explain joint effect of predictor variables on the dependent variable Y= β 0 + β 1 X 1 + β 2 X 2 + β 3 X 3 + β 4 X 4 + ε; Where; Where Y Profitability of deposit taking SACCOs measured as Net income divided by Total assets β 0 Y- intercept X 1 Loan performance management X 2 Fixed assets management 29
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X 3 Financial investments management X 4 Accounts receivables management β 1 , β 2 , β 3 & β 4 - Beta coefficients for the independent variables respectively ε Error term normally assumed to be randomly distributed 3.8 Ethical Consideration According to MulaG and Sarkar, S.C, (2013), ethics involves the study of right and wrong conduct. The researcher was very careful to avoid physical and psychological harm to the respondent in the process of data collection by not asking irrelevant or embarrassing questions (Mugenda and Mugenda, (2008). The researcher gave assurance to the respondents that the information collected would be kept confidential. The researcher informed the respondents that the purpose of the study was purely academic. The researcher exhibited moral character of an academician in the process of data collection period to get co-operation of respondents. The researcher encouraged a free corruption exercise by using mature people in data collection. This helped to keep the principle of confidentiality, avoidance of deception and anonymity, Sommer and Sommer, (2009). CHAPTER FOUR DATA ANALYSIS, INTERPRETATION AND PRESENTATION 4.1 Introduction This chapter presents the data analysis results, their presentation and interpretation. The chapter begins with the demographic characteristics of the respondents such as gender, age, academic qualifications, and years worked. Descriptive statistics are also presented. The results from the correlations and the regression analysis are also presented. 30
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4.2 Response Rate According to Babbie (1990), a response rate of 50% is adequate, 60% is good and 70% is very good for analysis and reporting from manual surveys. Table 4.1 below shows the response rate. Out of 110 questionnaires administered to the respondents, 82 were fully completed and returned making the response rate be 74.5%. This was above the expected response rate of 50-70% hence making it sufficient to perform data analysis of the research objectives.
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  • Fall '19
  • Balance Sheet, Generally Accepted Accounting Principles, Fixed asset, SACCOs

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