## Comparison of Means |
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## Assigned Reading- Comparison of means Read►
## PresentationsThere are three sets of presentations for this lecture: - Normal distribution Slides► Video► YouTube►
- Use Excel function for Z test YouTube►
- Introduction to Control Chart Slides► Listen►
- X-bar chart lecture Slides► Listen►
- XmR chart Slides► Listen►
- Risk Adjusted X-bar chart lecture Slides► Listen►
- Use Excel to create X-bar chart Excel 2003► Video► SWF►
- Use Excel to create risk adjusted X-bar chart Excel 2003►
- Dot plots and the mean Video►
- Histograms and shape How to► How to► Video►
- Two sample Z test Video►
- Calculating Z scores Video► Online Calculator►
Narrated slides and videos require Flash. ## Assignments
In these files the denominator indicates the number of patients. Payment indicates average payment per patient. Select data that meet the following conditions: - Select the "PAYM_30_AMI" measure
- Select hospitals who at start of 2015 had greater than national average payment. This information is provided in the field [Compared to National] in the file [HQI_HOSP_AMI_Payment ].
- Select hospitals that in the denominator do not have "Not Available".
- Examine if the payments to the hospitals changed over time. Create a control chart for the data.
Submit an Excel file containing the control chart for the data. Download►2016-11-10.zip► 2015-07-16.zip► 2015-01-22.zip► Guide► Answer► Anto's SQL►
- For all hospitals (not just those that were above national average payment in 2015), create a table containing the most recent payment and the previous time period's payment.
- Remove any hospital that did not have sufficient data in either time period.
- Calculate if the recent payment is different from payment in the previous time period.
- Test hypothesis that hospitals are receiving significantly higher payment at alpha levels less than 0.05. You can use Excel's paired t-test to carryout this test.
Submit SQL code, top 5 organizations with highest and lowest increase in payment, and result of your test of the hypothesis. Download►2016-11-10.zip► 2015-07-16.zip► 2015-01-22.zip►
Note that the field HBIPS-2_Overall_Num indicates the numerator for the measure "Hours of physical-restraint use." The denominator for the same overall measure is in the field HBIPS-2_Overall_Den. The dictionary provides the interpretation of these two fields as hours of restraint and number of patients examined. Using the procedure for XmR control chart examine if the total number of hours of restraints has changed over time. Download►2016-11-10.zip► 2016-08-10.zip► 2016-05-04.zip► 2015-12-10.zip► 2015-10-08.zip► 2015-07-16.zip► 2015-05-06.zip► 2015-04-16.zip► 2015-01-22.zip►Dictionary►
(a) Compute descriptive statistics for each variable. Check that you have not made an error in data entry and that your descriptive statistics match the following Excel output.
(b) Use Excel to perform a one sample test to evaluate whether or not the mean motivation level of all employees in the population is different from 5.
The null hypothesis is that µ1 = 5; i.e. the population mean motivation level
is equal to 5. The alternative hypothesis is that µ1 ≠ 5; i.e. the
population mean motivation level is significantly different from 5.
Calculate the mean (4.31) and the standard deviation (3.00) using functions
in Excel. Calculate the t-statistic and its degrees of freedom. Calculate
the critical value and test if the critical value is less than alpha of
0.05. Copy/paste relevant Excel output. Provide interpretation of "t" test results.
## More- Information on calculation of standard deviations Google►
- Annotated bibliography of using control charts to improve health care. PubMed►
- Student-t distribution More►
- Badii's lecture on normal distributions Part
1► Part
2►Slides►
**SPSS tutorial►** - Measures of central tendency Video►
**SPSS tutorial►**
This page is part of the course on Statistical Process Improvement, the lecture on Comparison of Means. This course was created by Farrokh Alemi, Ph.D. on January 22, 2016 |