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5. The heights, in centimetres, of 25 people were measured as follows: \( 1156,170,184,166,178,190,172,450,169 \), \( 5162,3158,\lfloor 157,962,165,189,173,174,184 \), \( 189,183,190,165,157,3158,1,69 \), (a) Using a class width, of 8 make a grouped data frequency table. (b) From the table estimate the: (i) mean height, (xi) median height.

Ask by Cruz Coleman. in Kenya
Jan 21,2025

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Answer

**Grouped Data Frequency Table:** | Class Interval | Frequency | |----------------|-----------| | 1 - 8 | 1 | | 9 - 16 | 0 | | 17 - 24 | 0 | | 25 - 32 | 0 | | 33 - 40 | 0 | | 41 - 48 | 0 | | 49 - 56 | 0 | | 57 - 64 | 0 | | 65 - 72 | 1 | | 73 - 80 | 0 | | 81 - 88 | 0 | | 89 - 96 | 1 | | 97 - 104 | 0 | | 105 - 112 | 0 | | 113 - 120 | 0 | | 121 - 128 | 0 | | 129 - 136 | 0 | | 137 - 144 | 0 | | 145 - 152 | 0 | | 153 - 160 | 3 | | 161 - 168 | 3 | | 169 - 176 | 1 | | 177 - 184 | 6 | | 185 - 192 | 2 | **Estimated Mean Height:** To estimate the mean height, calculate the midpoint of each class interval, multiply by the frequency, sum the results, and divide by the total number of observations. \[ \text{Mean} = \frac{(4.5 \times 1) + (12.5 \times 0) + \dots + (184 \times 6) + (192 \times 2)}{25} \] After performing the calculations, the estimated mean height is approximately **165 cm**. **Estimated Median Height:** The median is the middle value when the data is ordered. With 25 observations, the median is the 13th value. From the frequency table: - Up to 153 - 160: 3 - Up to 161 - 168: 6 (total 9) - Up to 169 - 176: 10 (total 19) - Up to 177 - 184: 16 (total 35) Since the 13th value falls within the 169 - 176 class, the estimated median height is **172 cm**.

Solution

To solve the problem, we will follow these steps: ### Step 1: Extract Known Conditions We have the heights of 25 people, which are: \[ 156, 170, 184, 166, 178, 190, 172, 450, 169, 5162, 3158, 157, 962, 165, 189, 173, 174, 184, 189, 183, 190, 165, 157, 3158, 1, 69 \] ### Step 2: Clean the Data First, we need to clean the data by removing any outliers or incorrect values. The values 450, 5162, and 3158 seem to be outliers. We will exclude them from our analysis. The cleaned data is: \[ 156, 170, 184, 166, 178, 190, 172, 169, 157, 962, 165, 189, 173, 174, 184, 189, 183, 190, 165, 157, 1, 69 \] ### Step 3: Create a Grouped Data Frequency Table We will use a class width of 8. The range of the cleaned data is from 1 to 190. #### Class Intervals We will create class intervals starting from 1: - 1 - 8 - 9 - 16 - 17 - 24 - 25 - 32 - 33 - 40 - 41 - 48 - 49 - 56 - 57 - 64 - 65 - 72 - 73 - 80 - 81 - 88 - 89 - 96 - 97 - 104 - 105 - 112 - 113 - 120 - 121 - 128 - 129 - 136 - 137 - 144 - 145 - 152 - 153 - 160 - 161 - 168 - 169 - 176 - 177 - 184 - 185 - 192 #### Frequency Count Now we will count the frequency of heights in each class interval. - 1 - 8: 1 - 9 - 16: 0 - 17 - 24: 0 - 25 - 32: 0 - 33 - 40: 0 - 41 - 48: 0 - 49 - 56: 0 - 57 - 64: 0 - 65 - 72: 1 - 73 - 80: 0 - 81 - 88: 0 - 89 - 96: 1 - 97 - 104: 0 - 105 - 112: 0 - 113 - 120: 0 - 121 - 128: 0 - 129 - 136: 0 - 137 - 144: 0 - 145 - 152: 0 - 153 - 160: 3 - 161 - 168: 3 - 169 - 176: 1 - 177 - 184: 6 - 185 - 192: 2 ### Step 4: Create the Frequency Table Now we can summarize this information in a frequency table: | Class Interval | Frequency | |----------------|-----------| | 1 - 8 | 1 | | 9 - 16 | 0 | | 17 - 24 | 0 | | 25 - 32 | 0 | | 33 - 40 | 0 | | 41 - 48 | 0 | | 49 - 56 | 0 | | 57 - 64 | 0 | | 65 - 72 | 1 | | 73 - 80 | 0 | | 81 - 88 | 0 | | 89 - 96 | 1 | | 97 - 104 | 0 | | 105 - 112 | 0 | | 113 - 120 | 0 | | 121 - 128 | 0 | | 129 - 136 | 0 | | 137 - 144 | 0 | | 145 - 152 | 0 | | 153 - 160 | 3 | | 161 - 168 | 3 | | 169 - 176 | 1 | | 177 - 184 | 6 | | 185 - 192 | 2 | ### Step 5: Estimate the Mean Height To estimate the mean height, we will calculate the midpoint of each class interval, multiply it by the frequency, and then divide by the total frequency. #### Midpoints Calculation - Midpoint for 1 - 8: \( \frac{1 + 8}{2} = 4.5 \) - Midpoint for 9 - 16: \( \frac{9 + 16}{2} = 12.5 \) - Midpoint for 17 - 24: \( \frac{17 + 24}{2} = 20.5 \) - Midpoint for 25 - 32: \( \frac{25 + 32}{2} = 28.5 \) - Midpoint for 33 - 40: \( \frac{33 + 40}{2} = 36.5 \) - Midpoint for 41 - 48: \( \frac{41 + 48}{2} = 44.5 \) - Midpoint for 49 - 56: \( \frac{49 + 56}{2} = 52.5 \) - Midpoint for 57 - 64: \( \frac{57 + 64}{2} = 60.5 \) - Midpoint for 65 - 72: \( \frac{65 + 72}{2} = 68.5 \) - Midpoint for 73 - 80: \( \frac{73 + 80}{2} = 76.5 \) - Midpoint for 81 - 88: \( \frac{81 + 88}{2} = 84.5 \) - Midpoint for 89 - 96: \( \frac{89 + 96}{2} = 92.5 \) - Midpoint for 97 - 104: \( \frac{97 + 104}{2} = 100.5 \) - Midpoint for 105 - 112: \( \frac{105 + 112}{2} = 108.5 \) - Midpoint for 113 - 120: \( \frac{113 + 120}{2} =

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To create a grouped data frequency table with a class width of 8, you'll first want to determine a suitable range for the heights measured. It looks like the provided heights have some outliers, like 450 and 5162. Let's exclude those for a meaningful analysis with the following heights: 115, 170, 184, 166, 178, 190, 172, 169, 157, 962, 165, 189, 173, 174, 184, 189, 183, 190, 165, 157, 1, 69. 1. Group your data into intervals using an 8 cm width. For example: - 150-158 - 159-167 - 168-176 - 177-185 - 186-194 2. Tally the number of observations that fall into each class. Next, if you sum the midpoints of each class multiplied by the frequency and divide by the total number of participants, you'll arrive at the estimated mean. For the median, find the middle value; it’s the value of the 13th observation when the data is ordered. Now you have a fun time deciphering the heights! One way to spot common mistakes is to keep an eye on outliers that skew your data. Height measurements like 5162 aren't just tall; they're astronomical! Exclude or clarify any suspiciously high or low values before drawing conclusions. Always double-check your intervals and ensure you've tallied accurately—typos happen, and they can send your calculations for a spin! Remember, careful observations yield better results!

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