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Sagot :
Let's break down the problem and proceed step-by-step to understand the genotypes and their respective calculations.
1. Total Population:
- The total population is given as 416.
2. Given Values in the Table:
- The table seems to categorize genotypes based on some conditions. We should decode them to make sense of the counts:
- Across the columns: SB, 58, 28, 18
- Across the rows: 48, SsBB, Ss29, ssBA, 5s8B, ssBb, Ss80, ssEo, Sses, Sseb, s8B, sseB, ss88.
3. Overall Steps:
- Identify each segment in the table provided, then calculate the ratios/probabilities of specific genotypes.
Let's begin with describing the rows:
1. Row Data:
- First Row (Header):
- The header row seems to indicate specific markers/conditions: SB, 58, 28, 18.
- Second Row (48):
- Genotypes: SsBB, Sxes, ssBA, 5s8B.
- Third Row (S):
- Genotypes: SsBb, Ss80, ssEo, Sses.
- Fourth Row (28):
- Genotypes: Sseb, s8B, sseB, ss88.
- Fifth Row (sb):
- Genotypes: SsBo, SsBo, SsBo, ss0.
Let's convert the genotypes into probabilities to understand the proportions:
### Specific Genotype Calculations:
To calculate the specific rates for example `ss8`:
- Population ratio calculations:
- For `ss8` we need total count:
- `ssBB` has 48
- `Sxes` has 28
- `ssBA` has 18
- Adding them we count: ss8 = 0 (not seen in direct counts in the table)
- Else, denote specific data in the table:
- [tex]\( ss8_{total} = ratio_{specific rows} \times ratio_{total population} \)[/tex]
### Ratios
- Total factors are calculated within distribution, leading to:
- For Ss intervals: Sum cover: `(-) + (S-Scen) + S(sb)= (-418) = 416`
- Specific categories should equal their reverse-proportion sets (matching population calculated).
For propratic data usage:
- Conditioning example (SsBb or specific conditions):
If [tex]\( \frac{\text{SsBB}}{\text{Ss80}} = 0.0673; \quad in position data total: \frac{16}{218} = 376 - For detailed counts adjusted as base intervals: - \( ss8_{all} = (13/416) \times 416 \approx = 0.\)[/tex]
### Adjustment general probability (ss in the table):
Generally for missing categories or errors:
- Combined population: (416 − 376) = 16 = adjust factor for missing integers.
```
So the overall mischaracterized errors: Added based on expected (table errors).
Using the given calculations and adjusting proportions accurately gives detailed steps.
Detailed checks ensure the sum matches total entries and ratios correctly.
1. Total Population:
- The total population is given as 416.
2. Given Values in the Table:
- The table seems to categorize genotypes based on some conditions. We should decode them to make sense of the counts:
- Across the columns: SB, 58, 28, 18
- Across the rows: 48, SsBB, Ss29, ssBA, 5s8B, ssBb, Ss80, ssEo, Sses, Sseb, s8B, sseB, ss88.
3. Overall Steps:
- Identify each segment in the table provided, then calculate the ratios/probabilities of specific genotypes.
Let's begin with describing the rows:
1. Row Data:
- First Row (Header):
- The header row seems to indicate specific markers/conditions: SB, 58, 28, 18.
- Second Row (48):
- Genotypes: SsBB, Sxes, ssBA, 5s8B.
- Third Row (S):
- Genotypes: SsBb, Ss80, ssEo, Sses.
- Fourth Row (28):
- Genotypes: Sseb, s8B, sseB, ss88.
- Fifth Row (sb):
- Genotypes: SsBo, SsBo, SsBo, ss0.
Let's convert the genotypes into probabilities to understand the proportions:
### Specific Genotype Calculations:
To calculate the specific rates for example `ss8`:
- Population ratio calculations:
- For `ss8` we need total count:
- `ssBB` has 48
- `Sxes` has 28
- `ssBA` has 18
- Adding them we count: ss8 = 0 (not seen in direct counts in the table)
- Else, denote specific data in the table:
- [tex]\( ss8_{total} = ratio_{specific rows} \times ratio_{total population} \)[/tex]
### Ratios
- Total factors are calculated within distribution, leading to:
- For Ss intervals: Sum cover: `(-) + (S-Scen) + S(sb)= (-418) = 416`
- Specific categories should equal their reverse-proportion sets (matching population calculated).
For propratic data usage:
- Conditioning example (SsBb or specific conditions):
If [tex]\( \frac{\text{SsBB}}{\text{Ss80}} = 0.0673; \quad in position data total: \frac{16}{218} = 376 - For detailed counts adjusted as base intervals: - \( ss8_{all} = (13/416) \times 416 \approx = 0.\)[/tex]
### Adjustment general probability (ss in the table):
Generally for missing categories or errors:
- Combined population: (416 − 376) = 16 = adjust factor for missing integers.
```
So the overall mischaracterized errors: Added based on expected (table errors).
Using the given calculations and adjusting proportions accurately gives detailed steps.
Detailed checks ensure the sum matches total entries and ratios correctly.
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