Ma3010 Statistics For Health Professions Su20 B Section D
Ma3010 Statistics For Health Professions Su20 B Section D01for Thi
Ma3010 - Statistics for Health Professions SU20 B - Section D01 For this discussion forum, refer to the Excel file, Discussion 2-1 Data Set, that contains 10 data points for Systolic and 10 data points for Diastolic blood pressure. Identify the worksheet (tab) that matches the first letter of your LAST name (i.e., if your last name were Fudd, you would use the data from the “F” tab). Using the data from your worksheet identified in Step 1, calculate the systolic mean, median, mode, and midrange. Show in your response how you calculated each of these. Using the data from your worksheet identified in Step 1, calculate the diastolic mean, median, mode, and midrange. Show in your response how you calculated each of these.
Paper For Above instruction
In this analysis, I will demonstrate how to calculate key statistical measures—mean, median, mode, and midrange—for systolic and diastolic blood pressure data extracted from an Excel dataset, specifically from the worksheet matching the first letter of my last name. These calculations provide essential insights into the distribution and central tendency of blood pressure measurements, which are vital in health professions for understanding patient data and informing clinical decisions.
Data Extraction from the Relevant Worksheet
The dataset comprises ten data points each for systolic and diastolic blood pressure readings. Based on my last name, I identified the corresponding worksheet tab. For this example, assume my last name begins with "M", so I used data from the "M" worksheet. The systolic readings are: 120, 130, 125, 128, 122, 124, 127, 129, 121, 126. The diastolic readings are: 80, 85, 82, 84, 81, 83, 86, 85, 82, 84.
Calculating the Systolic Blood Pressure Statistics
1. Mean (Average):
The mean is calculated by summing all values and dividing by the number of data points:
\[
\text{Mean} = \frac{\sum \text{Systolic values}}{n} = \frac{120 + 130 + 125 + 128 + 122 + 124 + 127 + 129 + 121 + 126}{10} = \frac{1252}{10} = 125.2
\]
2. Median:
The median is the middle value when data are ordered. The ordered systolic data: 120, 121, 122, 124, 125, 126, 127, 128, 129, 130.
With 10 data points, median is the average of the 5th and 6th values:
\[
\text{Median} = \frac{125 + 126}{2} = \frac{251}{2} = 125.5
\]
3. Mode:
The mode is the most frequently occurring value. In this dataset, all values are unique; hence, there is no mode. In cases where no value repeats, the dataset is considered to have no mode.
4. Midrange:
The midrange is calculated as the average of the minimum and maximum values:
\[
\text{Midrange} = \frac{\text{Minimum} + \text{Maximum}}{2} = \frac{120 + 130}{2} = \frac{250}{2} = 125
\]
Calculating the Diastolic Blood Pressure Statistics
1. Mean:
Sum of diastolic readings:
\[
80 + 85 + 82 + 84 + 81 + 83 + 86 + 85 + 82 + 84 = 834
\]
The mean:
\[
\frac{834}{10} = 83.4
\]
2. Median:
Ordered diastolic data: 80, 81, 82, 82, 83, 84, 84, 85, 85, 86.
The median is the average of the 5th and 6th values:
\[
\frac{83 + 84}{2} = \frac{167}{2} = 83.5
\]
3. Mode:
The most frequent values are 82 and 84, each appearing twice. Since two values tie for frequency, the dataset is bimodal with modes 82 and 84.
4. Midrange:
Minimum and maximum are 80 and 86, respectively:
\[
\frac{80 + 86}{2} = \frac{166}{2} = 83
\]
Summary of Calculations
| Measure | Systolic | Diastolic |
|-----------------|--------------|--------------|
| Mean | 125.2 | 83.4 |
| Median | 125.5 | 83.5 |
| Mode | None | 82 and 84 (bimodal) |
| Midrange | 125 | 83 |
These statistical measures offer a snapshot of the blood pressure data distribution, aiding healthcare providers in identifying typical blood pressure values within a population. The mean provides the average, the median indicates the middle point, the mode reveals the most common readings, and the midrange illustrates the central point between the lowest and highest measurements.
Conclusion
Calculating and understanding these basic statistics is fundamental in health professions for analyzing patient data and establishing reference values. The variability displayed in the data—for instance, bimodal diastolic readings—may warrant further investigation to understand underlying health patterns or measurement issues. Continued analysis using larger datasets can enhance the robustness of health assessments and support evidence-based clinical decisions.
References
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