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Respondents Sex Statistic Std. Error 6.33 5.12 7.54 4.85 2.00 90.364 9.506 EmailHrsiperWeek Male Mean 95%...
Respondents Sex Statistic Std. Error 6.33 5.12 7.54 4.85 2.00 90.364 9.506 EmailHrsiperWeek Male Mean 95%...
Respondents Sex Statistic Std. Error 6.33 5.12 7.54 4.85 2.00 90.364 9.506 EmailHrsiperWeek Male Mean 95% Confidence Interval for Mean 5% Trimmed Mean Median Variance Std. Deviation Minimum Maximum Range Interquartile Range Skewness Kurtosis 615 Lower Bound Upper Bound 50 50 2.658 7.585 5.93 4.98 6.88 4.57 2.00 78.924 8.884 157 314 485 Female Mean 95% Confidence Interval for Mean 5% Trimmed Mean Median Variance Std. Deviation Minimum Maximum Range Interquartile Range Skewness Kurtosis Lower Bound Upper Bound 50 50...
Respondents Sex Statistic Std. Error 6.33 5.12 7.54 4.85 2.00 90.364 9.506 EmailHrsiperWeek Male Mean 95%...
Respondents Sex Statistic Std. Error 6.33 5.12 7.54 4.85 2.00 90.364 9.506 EmailHrsiperWeek Male Mean 95% Confidence Interval for Mean 5% Trimmed Mean Median Variance Std. Deviation Minimum Maximum Range Interquartile Range Skewness Kurtosis 615 Lower Bound Upper Bound 50 50 2.658 7.585 5.93 4.98 6.88 4.57 2.00 78.924 8.884 157 314 485 Female Mean 95% Confidence Interval for Mean 5% Trimmed Mean Median Variance Std. Deviation Minimum Maximum Range Interquartile Range Skewness Kurtosis Lower Bound Upper Bound 50 50...
Quick Check please Respondents Sex Statistic Std. Error 6.33 5.12 7.54 4.85 2.00 90.364 9.506 EmailHrsiperWeek...
Quick Check please
Respondents Sex Statistic Std. Error 6.33 5.12 7.54 4.85 2.00 90.364 9.506 EmailHrsiperWeek Male Mean 95% Confidence Interval for Mean 5% Trimmed Mean Median Variance Std. Deviation Minimum Maximum Range Interquartile Range Skewness Kurtosis 615 Lower Bound Upper Bound 50 50 2.658 7.585 5.93 4.98 6.88 4.57 2.00 78.924 8.884 157 314 485 Female Mean 95% Confidence Interval for Mean 5% Trimmed Mean Median Variance Std. Deviation Minimum Maximum Range Interquartile Range Skewness Kurtosis Lower Bound Upper...
What does the five number tell us about the time spent on email (Hint, interpret the...
What does the five number tell us about the time spent on email
(Hint, interpret the five number summary in plain English) and what
does the Boxplot and the normality test show? Explain.
Use the 1.5xIQR rule to identify possible outliers. List the
cutoff points for outliers, Show your workings. Explain what you
found out. (Hint: Are there any excessive time spent on email for
Male(1) or Female(2) or both).
GET DATA /TYPE-XLS /FILE='C: \Users\rmanda 1 \ Desktop\homework! . xls'...
4. Use the following charts to compare the central tendency and variability between men and women...
4. Use the following charts to compare the central tendency and variability between men and women for the variable AGEKDBRN and answer the following questions. Case Processing Summary Cases Missing Valid Total sex RESPONDENTS SEX 1 MALE 2 FEMALE Percent 601 | 67.5% 869| 75.4% Percent 891 | 100.0% 284 | 24.6% | 1153 | 100.0% Percent 2901 32.5% WHEN 1ST CHILD BORN Descriptives StatisticStd. Error 269 agekdbrn RS AGE WHEN 1ST CHILD BORN 25.54 25.02 Upper Bound 26.07 25.13...
Below are numerical and graphical summaries of Price. Use these to complete Questions 7 and 8....
Below are numerical and graphical summaries of Price. Use these to complete Questions 7 and 8. Descriptives Statistic Std. Error price Mean 80.7500 4.98105 95% Confidence Interval Lower Bound 70.8355 for Mean Upper Bound 90.6645 Median 73.9750 Variance 1984.867 Std. Deviation 44.55184 Minimum 9.99 Maximum 249.00 Range 239.01 Interquartile Range 47.29 Frequency 25 50 75 175 200 225 250 100 125 150 price 7. Consider the variable Price. A. Complete the table below. Mean Median Standard deviation Sample size B....
A study was conducted to evaluate the effectiveness of a weight loss program. Among 36 obese indi...
A study was conducted to evaluate the effectiveness of a weight loss program. Among 36 obese individuals aged 55 to 75 years randomly selected into the study, each individual had his/her BMI computed before and after the program. The decrease in the BMI was recorded into a SAS dataset and proc univariate was used to analyze this dataset. The population m ean of the decrease in the BMI is denoted by μ. Use the SAS output on the following page...
Respondents Sex Statistic Std. Error 6.33 5.12 7.54 4.85 2.00 90.364 9.506 EmailHrsiperWeek Male Mean 95% Confidence Interval for Mean 5% Trimmed Mean Median Variance Std. Deviation Minimum Maximum Range Interquartile Range Skewness Kurtosis 615 Lower Bound Upper Bound 50 50 2.658 7.585 5.93 4.98 6.88 4.57 2.00 78.924 8.884 157 314 485 Female Mean 95% Confidence Interval for Mean 5% Trimmed Mean Median Variance Std. Deviation Minimum Maximum Range Interquartile Range Skewness Kurtosis Lower Bound Upper Bound 50 50...
Respondents Sex Statistic Std. Error 6.33 5.12 7.54 4.85 2.00 90.364 9.506 EmailHrsiperWeek Male Mean 95% Confidence Interval for Mean 5% Trimmed Mean Median Variance Std. Deviation Minimum Maximum Range Interquartile Range Skewness Kurtosis 615 Lower Bound Upper Bound 50 50 2.658 7.585 5.93 4.98 6.88 4.57 2.00 78.924 8.884 157 314 485 Female Mean 95% Confidence Interval for Mean 5% Trimmed Mean Median Variance Std. Deviation Minimum Maximum Range Interquartile Range Skewness Kurtosis Lower Bound Upper Bound 50 50...
Quick Check please
Respondents Sex Statistic Std. Error 6.33 5.12 7.54 4.85 2.00 90.364 9.506 EmailHrsiperWeek Male Mean 95% Confidence Interval for Mean 5% Trimmed Mean Median Variance Std. Deviation Minimum Maximum Range Interquartile Range Skewness Kurtosis 615 Lower Bound Upper Bound 50 50 2.658 7.585 5.93 4.98 6.88 4.57 2.00 78.924 8.884 157 314 485 Female Mean 95% Confidence Interval for Mean 5% Trimmed Mean Median Variance Std. Deviation Minimum Maximum Range Interquartile Range Skewness Kurtosis Lower Bound Upper...
What does the five number tell us about the time spent on email
(Hint, interpret the five number summary in plain English) and what
does the Boxplot and the normality test show? Explain.
Use the 1.5xIQR rule to identify possible outliers. List the
cutoff points for outliers, Show your workings. Explain what you
found out. (Hint: Are there any excessive time spent on email for
Male(1) or Female(2) or both).
GET DATA /TYPE-XLS /FILE='C: \Users\rmanda 1 \ Desktop\homework! . xls'...
4. Use the following charts to compare the central tendency and variability between men and women for the variable AGEKDBRN and answer the following questions. Case Processing Summary Cases Missing Valid Total sex RESPONDENTS SEX 1 MALE 2 FEMALE Percent 601 | 67.5% 869| 75.4% Percent 891 | 100.0% 284 | 24.6% | 1153 | 100.0% Percent 2901 32.5% WHEN 1ST CHILD BORN Descriptives StatisticStd. Error 269 agekdbrn RS AGE WHEN 1ST CHILD BORN 25.54 25.02 Upper Bound 26.07 25.13...
Below are numerical and graphical summaries of Price. Use these to complete Questions 7 and 8. Descriptives Statistic Std. Error price Mean 80.7500 4.98105 95% Confidence Interval Lower Bound 70.8355 for Mean Upper Bound 90.6645 Median 73.9750 Variance 1984.867 Std. Deviation 44.55184 Minimum 9.99 Maximum 249.00 Range 239.01 Interquartile Range 47.29 Frequency 25 50 75 175 200 225 250 100 125 150 price 7. Consider the variable Price. A. Complete the table below. Mean Median Standard deviation Sample size B....
A study was conducted to evaluate the effectiveness of a weight loss program. Among 36 obese individuals aged 55 to 75 years randomly selected into the study, each individual had his/her BMI computed before and after the program. The decrease in the BMI was recorded into a SAS dataset and proc univariate was used to analyze this dataset. The population m ean of the decrease in the BMI is denoted by μ. Use the SAS output on the following page...
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