澳洲数学assignment代写:商业分析线性回归模型
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Thermata是一家因良好的客户关系而成长和繁荣的公司,其中包括合作、按时交付高质量的产品以及倾听客户的需求。假设公司管理层希望每年至少正式测量一次客户满意度,并制定一份简短的调查报告,其中包括以下四个问题。假设有115位顾客参与了这项调查,结果如下。通过寻找置信区间(α=0.05)来分析数据,以估计四个问题中每一个问题的(正)总体响应。提供你对结果的解释和讨论。
现在假设Thermata官员想确定员工对公司的满意度。他们随机抽取了9名员工,要求他们在独立测试机构的监督下完成满意度调查。作为这项调查的一部分,员工被要求以5分制回答问题,其中1分为低满意度,5分为高满意度。
问题和调查结果将在下一列中列出。通过寻找置信区间(α=0.05)来分析数据,以估计人群对这些问题的反应。提供你对结果的解释和讨论。
请参阅housingmarket.csv文件中为此问题提供的数据。建立最佳线性回归模型,根据房屋的特点和邻里关系的特点来预测房屋的中值。讨论结果。(提示:你的讨论应该包括模型有多好,房价的重要预测因素是什么,这些预测因素与房价有什么关系,数据/模型是否有我们应该注意的问题……)必要时,你需要用数字和表格来支持你的答案。
澳洲数学
assignment代写:商业分析线性回归模型
INFS3873Business Analytics Methods
Thermata is company that has grown and flourished because of its good customer relationships, which include partnering, delivering a quality product on time, and listening to the customer’s needs. Suppose company management wants to formally measure customer satisfaction at least once a year and develops a brief survey that includes the following four questions. Suppose 115 customers participated in this survey with the result shown. Analyse the data by finding a confidence interval (with =0.05) to estimate the(positive) population response to each of the four questions. Provide your interpretation and discussions of the results.
Now suppose Thermata officers want to ascertain employee satisfaction with the company. They randomly sample nine employees and ask them to complete a satisfaction survey under the supervision of an independent testing organisation. As part of this survey, employees are asked to respond to questions on a 5-point scale where 1 is low satisfaction and 5 is high satisfaction.
The questions and the results of the survey are shown in the next column. Analyse the data by finding a confidence interval (with =0.05) to estimate the population response to each of these questions. Provide your interpretation and discussions of the results.
se the data provided in the housingmarket.csv file for this question. Develop the best possible linear regression model to predict the median value of the house based on its characteristics as well as the neiborhood characteristics. Discuss the results. (Hint: Your discussion should include how good the model is, what are the important predictors of house prices, how do these predictors relate to house prices, are there any issues with the data/model that we should be aware of…). You will need to support your answer with figures and tables when necessary.
INFS3873Business Analytics Methods
澳洲数学assignment代写:商业分析线性回归模型