Descriptives Product Quality Competitive_Price Accessability Advertising Capability Valid N (listwise) Descriptive Statistics Minimum Maximum 5.00 10.00 1.30 8.50 1.90 6.50 3.70 9.90 N 100 100 100 100 100 DESCRIPTIVES VARIABLES=Customer Satisfaction /STATISTICS=MEAN STDDEV MIN MAX. Mean 7.8100 5.3650 4.0100 6.9740 Std. Deviation 1.39628 1.53046 1.12694 1.54506
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- corse of quality statisticWhat are the available point estimator andestimate of the population mean starting salary?Price_($000)/Sq Ft 1/Sq Ft Location 14.0542 0.0653 0 17.2907 0.0524 0 18.3029 0.00649 0 15.7341 0.04374 0 14.8521 0.01913 0 15.3572 0.0197 0 18.3278 0.01583 0 15.8483 0.41563 0 17.392 0.29976 0 15.8826 0.1798 0 15.5492 0.00816 0 14.619 0.0325 0 15.7633 0.21829 0 15.1289 0.015939 0 17.2874 0.18765 0 15.6938 0.00986 0 15.3672 0.03096 0 15.3126 0.01917 0 17.4008 0.06055 0 16.1066 0.0611 0 16.6637 0.1171 1 16.5504 0.05552 1 17.0575 0.00657 1 17.9466 0.1407 1 17.8913 0.0648 1 15.5396 0.03339 1 18.6629 0.03443 1 18.0774 0.019 1 20.8122 0.20162 1 18.3237 0.319 1
- The mean for cat-OreDock condition should be?What is the average score for meeting project deadlines with the standard deviation?Which of the following statements about descriptive analysis is FALSE? * for most projects, statistical analysis begins by data cleaning and data transformation to reduce the raw data into a summary format. tabulation refers to the orderly arrangement of data in a table in rows and columns format. analyzing results by groups or categories is the technique of tabulation. descriptive analysis gives you an idea of the distribution of your data, helps you detect outliers and typos thus making you ready to conduct further statistical analyses.
- What is the most frequent number of over-the-limit items for this data set? ans = What is the frequency of the most frequent number of over-the-limit items? ans =Outliers (z-scores) Outliers are points that are ``further away" from the other data points or possibly ``further away" from the trend or pattern for the other data. The precise line used for determining what is ``further away" is sometimes subject to judgement and can vary depending on context and goals. [NOTE: Not every data set will have outliers.] One means of measuring to determine where the outliers are is use of the Z-score (the number of standard deviations away from the center). If the data is mound-shaped (largest amount concentrated near the middle), then a Z-score of Z > 3.0 OR of Z < - 3.0 would clearly be in the range for outliers. [See empirical rule later.] Suppose a set of data is mound-shaped and has a mean of and standard deviation of . { (mu) = 72, (sigma) = 8.0 } For each of the following data points, find the Z-score and classify whether the point should be considered an outlier. a) xi = 93 b) xi = 98 c) xi = 45 d) xi = 52Why might the range not be the best estimate of variablitiy?