Choose Any Published Database From The Internet Such As Thos
Choose Any Published Database From The Internet Such As Those From Th
Choose any published database from the internet (such as those from the Census Bureau or any financial or sports sites) or from your workplace. You may opt to use one of the data files provided by the instructor if applicable. Your chosen database must be pre-approved by the instructor. If the file is larger than 200 observations, randomly choose 200 observations from the data. Explain each variable in the file that you are analyzing. Be sure your file includes at least 3 scale variables and at least 2 nominal variables. Conduct a descriptive analysis on any 2 interval/ratio variables you wish using Descriptive_Statistics.xls and Frequency_Distribution.xls. Explain the output. Conduct 3 different hypothesis tests of your choice using appropriate variables from the file (note: you must use 3 different tests and not run one test on 3 different variables). In each case, state the variables being tested as well as the hypothesis, decision, and conclusion. Use 3 of the following (1-Sample Test for Means, 1-Sample Test for Proportions, 2-Sample Test for Means – Independent Samples, 2-Sample Test for Means – Paired Samples, 2-Sample Test for Proportions, Analysis of Variance, Chi Square Goodness of Fit Test, Chi Square Test of Independence, Correlation Test). Develop a model to predict an interval/ratio variable using at least 2 other variables. Use Multiple_Regression.xls and state the regression model and which variables are or are not significant. Also, use the model to make a prediction by making up values for each of the independent variables. Write a one to two page summary of your findings. Include the data file in the appendix. Comments in which you describe your findings should be included with each display. The assignment should be formatted professionally and adhere to good written English.
Paper For Above instruction
The task involves selecting a publicly available database from the internet, such as data from the Census Bureau, financial, or sports websites, or alternatively from personal or workplace data. The initial step is to ensure the dataset is approved by the instructor, with a maximum of 200 observations if the dataset exceeds this number. The chosen dataset must include at least five variables, specifically three scale (interval/ratio) and two nominal variables, which will be clearly described to understand the context and nature of each variable in the analysis.
Following the selection and description of the dataset, a descriptive statistical analysis is performed on two selected ratio/interval variables. This involves calculating measures such as mean, median, standard deviation, and possibly skewness and kurtosis, using Excel tools like Descriptive_Statistics.xls and Frequency_Distribution.xls. The outputs from these analyses are interpreted to understand the distribution, central tendency, and dispersion of the variables, providing foundational insights into the data's characteristics.
The subsequent phase involves conducting three hypothesis tests with distinct purposes and methods. These include, but are not limited to, a one-sample test for means, a chi-squared test of independence, and a correlation test. Each test is clearly formulated with a null and alternative hypothesis, followed by the decision rule, and conclusion based on the test results. For example, testing whether the average income exceeds a certain level or whether two categorical variables are independent. Proper selection of test types ensures appropriate analysis based on variable types and research questions.
Next, a predictive modeling process is undertaken. Using multiple linear regression analysis with the aid of the Multiple_Regression.xls tool, an interval or ratio variable is modeled as a function of at least two other variables. The regression output specifies which independent variables are statistically significant predictors. Based on the regression model, predictions are made by inputting hypothetical values for the independent variables. This step synthesizes the analysis to generate practical insights or forecasts relevant to the dataset's context.
Finally, a comprehensive one- or two-page report consolidates all findings. This report presents the descriptive insights, hypothesis test outcomes, and the regression modeling results, including the prediction example. Each analysis is explained clearly, emphasizing the implications and relevance of the findings. The data file is appended at the end, formatted professionally, with narrative descriptions accompanying each display to ensure clarity and coherence. Proper English, punctuation, and grammar are maintained throughout to meet academic standards.