**Q2: **

A coin is biased with a chance of getting tails for every random toss. Estimate the probability of getting exactly 55 heads in 100 tosses of a coin.

**Q3: **

A number cube is rolled 127 times. The results are recorded in the following table. What is the experimental probability of rolling a number greater than 4?

Number | 1 | 2 | 3 | 4 | 5 | 6 |
---|---|---|---|---|---|---|

Occurrence | 21 | 21 | 14 | 29 | 15 | 27 |

- A
- B
- C
- D
- E

**Q4: **

A survey of 92 people found that 55 people support Team A, 30 people support Team B, and 7 people support neither. What is the probability that a person supports Team A?

- A
- B
- C
- D
- E

**Q5: **

A sample of 64 people found that 36 of them watch Channel A, 29 of them watch Channel B, and 11 watch both channels. What is the probability that a random person from the sample only watches Channel A?

- A
- B
- C
- D
- E

**Q6: **

A factory produces two types of televisions and wants to decide how many of each to produce. The table shows the sales of a sample of 50 TV sets from each of 5 shopping malls. If the factory is going to produce 6 000 TV sets in total, how many should be of Type B?

Number of Shopping Mall | 1 | 2 | 3 | 4 | 5 |
---|---|---|---|---|---|

Sales of Type A | 16 | 36 | 34 | 14 | 15 |

Sales of Type B | 34 | 14 | 16 | 36 | 35 |

- A 4 320
- B 2 760
- C 1 680
- D 3 240

**Q7: **

A company that manufactures light bulbs tests a sample of 1000 light bulbs to determine their lifespan. The results are shown in the table. What is the probability that a light bulb lasts at least 400 hours?

(Maximum Working Hours) | Less than 150 | More than 1000 | ||
---|---|---|---|---|

Number of Lamps | 100 | 320 | 270 | 310 |

- A
- B
- C
- D
- E

**Q8: **

Three fair coins are flipped. What is the probability that as many heads as tails appear?

**Q9: **

A life insurance company used a sample of 4 000 men between the ages of 50 and 60 to find the probability of a man dying between these ages. Given that 17 men in the sample died, calculate the experimental probability of a man dying between the ages of 50 and 60.