/*! This file is auto-generated */ .wp-block-button__link{color:#fff;background-color:#32373c;border-radius:9999px;box-shadow:none;text-decoration:none;padding:calc(.667em + 2px) calc(1.333em + 2px);font-size:1.125em}.wp-block-file__button{background:#32373c;color:#fff;text-decoration:none} Problem 8 Make a list of all possible outc... [FREE SOLUTION] | 91Ó°ÊÓ

91Ó°ÊÓ

Make a list of all possible outcomes for gender when a family has two children. Assume that the probability of having a boy is \(0.50\) and the probability of having a girl is also \(0.50\). Find the probability of each outcome in your list.

Short Answer

Expert verified
The probability of each outcome Boy - Boy, Boy - Girl, Girl - Boy, Girl - Girl is equal to 0.25 or 25%.

Step by step solution

01

List all Possible Outcomes

The possible combinations for a two-child family regarding gender are: Boy - Boy, Boy - Girl, Girl - Boy, Girl - Girl.
02

Assign Probabilities

Using the probability of \(0.50\) for both genders: \n The combination Boy - Boy has \(0.50 \times 0.50 = 0.25\) or \(25\%\) \n The combination Boy - Girl has \(0.50 \times 0.50 = 0.25\) or \(25\%\) \n The combination Girl - Boy has \(0.50 \times 0.50 = 0.25\) or \(25\%\) \n The combination Girl - Girl has \(0.50 \times 0.50 = 0.25\) or \(25\%\)
03

Confirm Total Probability is 1

\n Adding up the probabilities: \(0.25 + 0.25 + 0.25 + 0.25 = 1.00\) or \(100\%\). The sum of all the probabilities is 1 which confirms that all outcomes have been accounted correctly.

Unlock Step-by-Step Solutions & Ace Your Exams!

  • Full Textbook Solutions

    Get detailed explanations and key concepts

  • Unlimited Al creation

    Al flashcards, explanations, exams and more...

  • Ads-free access

    To over 500 millions flashcards

  • Money-back guarantee

    We refund you if you fail your exam.

Over 30 million students worldwide already upgrade their learning with 91Ó°ÊÓ!

Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Understanding Outcomes
When talking about probability, an **outcome** is simply a possible result of an experiment or situation. In our example of a family with two children, each child being either a boy (B) or a girl (G), there are a certain number of possible outcomes based on the combinations of these genders.

To determine the possible outcomes when two children are born in a family, consider each individual child's gender possibility. Each child has two options: boy or girl. Therefore, for two children you can have combinations as follows:
  • Boy - Boy (BB)
  • Boy - Girl (BG)
  • Girl - Boy (GB)
  • Girl - Girl (GG)
Each of these outcomes is unique, and together they form the complete set of possibilities for this situation. Understanding these outcomes helps in further exploring how probable each one is, thereby leading into probability distribution.
Exploring Probability Distribution
Once we grasp the possible outcomes, the next step is to determine how often you might expect each outcome to occur — this is known as the **probability distribution**. For our example, we have four outcomes, each occurring with the same probability.

To find this probability, you multiply the separate probabilities of each child being a boy or a girl. Given that the probability of either child being a boy or a girl is equal, i.e., \(0.50\), calculating the probability for each listed outcome involves:
  • Probability of Boy-Boy: \(0.50 \times 0.50 = 0.25\)
  • Probability of Boy-Girl: \(0.50 \times 0.50 = 0.25\)
  • Probability of Girl-Boy: \(0.50 \times 0.50 = 0.25\)
  • Probability of Girl-Girl: \(0.50 \times 0.50 = 0.25\)
The sum of these probabilities \(0.25 + 0.25 + 0.25 + 0.25 = 1.00\) assures us that our distribution covers all possible outcomes. This balance across likely outcomes confirms that our understanding of the situation is complete and accurate.
Applying Combinatorics
**Combinatorics** is the branch of mathematics dealing with combinations of objects. It's an essential tool for counting possible outcomes. In our two-child family scenario, combinatorics simplifies the process of determining outcome possibilities.

In combinatorics, when calculating the number of possible outcomes, you often use the counting principle. It tells you that for every option there is another set of choices to consider. For instance, with two children and two gender possibilities per child:
  • The first child can be a boy or a girl; this gives 2 possibilities.
  • The second child can also be a boy or a girl, again providing 2 possibilities.
By multiplying these possibilities together, you get the total number of outcomes: \(2 \times 2 = 4\).

Thus, combinatorics facilitates understanding how different combinations arise, confirming our outcomes: Boy-Boy, Boy-Girl, Girl-Boy, and Girl-Girl. This systematic approach of counting ensures that all the variables are considered, making it a vital methodology in probability calculations.

One App. One Place for Learning.

All the tools & learning materials you need for study success - in one app.

Get started for free

Most popular questions from this chapter

According to Anthropometric Survey data, the distribution of arm spans for males is approximately Normal with a mean of \(71.4\) inches and a standard deviation of 3. 3 inches. a. What percentage of men have arm spans between 66 and 76 inches? b. Professional basketball player, Kevin Durant, has an arm span of almost 89 inches. Find the \(z\) -score for Durant's arm span. What percentage of males have an arm span at least as long as Durant's?

The Normal model \(N(69,3)\) describes the distribution of male heights in the United States. Which of the following questions asks for a probability, and which asks for a measurement? Identify the type of problem and then answer the given question. See page 316 for guidance. a. To be a member of the Tall Club of Silicon Valley a man must be at least 74 inches tall. What percentage of men would qualify for membership in this club? b. Suppose the Tall Club of Silicon Valley wanted to admit the tallest \(2 \%\) of men. What minimum height requirement should the club set for its membership criteria?

For each question, find the area to the right of the given \(z\) -score in a standard Normal distribution. In this question, round your answers to the nearest \(0.000\). Include an appropriately labeled sketch of the \(N(0,1)\) curve. a. \(z=-4.00\) b. \(z=-8.00\) c. \(z=-30.00\) d. If you had the exact probability for these right proportions, which would be the largest and which would be the smallest? e. Which is equal to the area in part b: the area below (to the left of) \(z=8.00\) or the area above (to the right of) \(z=8.00\) ?

In a standard Normal distribution, if the area to the left of a \(z\) -score is about \(0.1000\), what is the approximate \(z\) -score?

Babies in the United States have a mean birth length of \(20.5\) inches with a standard deviation of \(0.90\) inch. The shape of the distribution of birth lengths is approximately Normal. a. How long is a baby born at the 20 th percentile? b. How long is a baby born at the 50 th percentile? c. How does your answer to part b compare to the mean birth length? Why should you have expected this?

See all solutions

Recommended explanations on Math Textbooks

View all explanations

What do you think about this solution?

We value your feedback to improve our textbook solutions.

Study anywhere. Anytime. Across all devices.