Confidence Intervals for Heart Rate Data.

Calculating Confidence Intervals for Quantitative Variables in Heart Rate Dataset

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In this assignment, you will calculate confidence intervals for the quantitative variables in the Heart Rate Dataset. Steps Open the Heart Rate Dataset in Excel and identify the quantitative variables Make sure the data is sorted by category (e.g.male-at-rest, female at-rest, etc.)

Use the Data Analysis tools of Excel to construct 95% and 99% confidence intervals for all 8 categories of the sorted quantitative variables. Excel will calculate the margin of error given as the “confidence interval” in the output. Use this margin of error to create your 8 confidence intervals by both adding and subtracting it from the sample mean (calculated in unit 3).

This creates a range of values that is the confidence interval. Create a Word document, and use your calculated results to explain what the confidence intervals tell us.

What do these confidence intervals tell us about our heart rate data?

How would you interpret the 95% and 99% intervals for resting heart rate?

Compare the 99% and 95% intervals and explain why one is larger than the other even though we use the same sample mean value.

M=0 F=1	Resting	After Exercise
0	55.0	65.0
0	67.7	79.4
0	80.3	93.4
0	85.2	97.7
0	86.3	99.7
0	76.6	83.7
0	94.4	101.9
0	86.4	100.6
0	83.4	97.4
0	89.8	97.4
0	88.7	97.1
0	78.4	87.2
0	67.0	79.9
0	85.0	100.0
0	86.2	95.9
0	83.9	93.9
0	78.1	87.2
0	64.0	70.7
0	72.8	86.7
0	65.0	75.0
0	80.2	83.3
0	78.2	86.0
0	62.0	88.0
0	75.5	84.4
0	82.7	89.1
0	87.7	95.1
0	76.0	88.7
0	73.4	82.7
0	80.1	94.6
0	77.6	84.6
0	76.6	86.4
0	85.6	96.2
0	74.2	82.1
0	79.0	91.6
0	74.6	86.7
0	88.8	98.8
0	82.1	85.6
0	77.6	80.6
0	77.9	83.8
0	72.0	93.9
0	81.6	90.3
0	91.2	100.6
0	80.3	88.0
0	76.7	91.8
0	88.4	103.0
0	75.2	86.5
0	75.2	84.9
0	73.1	71.9
0	77.0	84.7
0	59.0	68.2
0	84.9	96.0
0	87.5	105.9
0	75.6	84.3
0	84.0	90.4
0	78.2	94.0
0	86.6	90.6
0	84.9	95.1
0	78.8	90.4
0	69.4	82.6
0	78.3	91.1
0	76.9	92.3
0	84.2	87.9
0	76.3	85.9
0	86.3	99.7
0	72.3	80.9
0	81.8	93.8
0	92.8	99.8
0	74.8	90.2
0	91.7	99.2
0	71.0	87.0
0	96.1	100.2
0	82.5	95.1
0	81.9	97.5
0	89.7	94.8
0	81.4	100.9
0	74.8	94.0
0	88.1	102.1
0	69.2	81.4
0	78.8	90.9
0	85.3	94.2
0	74.8	81.3
0	77.7	89.9
0	78.0	89.8
0	80.5	95.3
0	75.4	84.8
0	81.5	84.2
0	73.9	85.2
0	69.4	74.1
0	89.4	96.7
0	70.9	82.0
0	82.9	90.2
0	60.1	79.0
0	74.5	75.6
0	92.3	102.2
0	87.7	98.0
0	78.9	89.7
0	79.8	81.5
0	85.5	97.4
0	87.3	94.1
0	77.8	97.8
0	71.0	80.1
0	70.0	90.7
0	74.8	83.7
0	69.2	79.4
0	80.5	87.4
0	89.4	99.2
0	74.5	88.0
0	70.0	100.0
1	60.0	78.1
1	79.2	90.4
1	80.5	101.3
1	75.4	93.1
1	83.7	90.5
1	73.9	89.1
1	76.0	90.8
1	85.2	93.5
1	82.1	93.5
1	76.3	87.0
1	97.0	104.5
1	81.5	86.5
1	65.3	86.3
1	60.8	86.7
1	78.5	89.9
1	60.4	97.6
1	89.8	92.9
1	87.8	98.5
1	76.2	89.9
1	74.2	88.8
1	67.4	78.8
1	75.5	80.2
1	80.0	90.2
1	76.4	88.0
1	60.0	95.7
1	89.2	96.9
1	83.3	87.7
1	85.8	90.4
1	75.3	84.1
1	77.9	99.0
1	70.0	83.0
1	88.0	94.2
1	86.9	95.0
1	87.1	95.9
1	60.3	82.7
1	81.2	90.7
1	82.9	91.9
1	87.4	103.6
1	83.0	90.0
1	76.8	83.3
1	76.9	87.7
1	79.8	88.2
1	83.2	93.0
1	79.5	88.6
1	82.4	89.3
1	80.8	84.2
1	83.2	94.5
1	71.6	81.5
1	82.8	93.1
1	76.8	92.8
1	93.2	89.4
1	91.4	100.9
1	97.3	103.3
1	88.3	90.1
1	80.6	85.2
1	87.4	91.7
1	96.5	99.3
1	77.9	91.6
1	76.1	84.1
1	85.2	89.7
1	68.6	72.8
1	79.4	91.0
1	85.2	99.1
1	74.3	85.6
1	74.3	89.2
1	78.5	98.5
1	80.4	90.8
1	82.9	85.9
1	78.9	90.7
1	78.6	87.0
1	87.5	93.9
1	78.9	91.4
1	80.0	89.1
1	80.4	89.2
1	88.3	90.5
1	80.6	95.9
1	85.8	90.5
1	84.6	93.0
1	90.5	101.2
1	92.4	101.2
1	84.4	96.7
1	82.3	86.9
1	77.2	85.8
1	83.3	82.1
1	86.2	98.9
1	81.3	97.7
1	90.2	96.4
1	78.4	85.5
1	84.7	90.9
1	89.7	94.3
1	78.4	88.0
1	70.0	80.0

Count	200		Average	79.7	90.2
Female	92.0	46%
Male	108.0	54%

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