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A roulette wheel consists of 38 numbers, 0 through 36 and \(00 .\) Of these, 18 numbers are red, 18 are black, and 2 are green ( 0 and 00 ). You are given \(\$ 10\) and told that you must pick one of two wagers, for an outcome based on a spin of the wheel: (1) Bet \(\$ 10\) on number 23\. If the spin results in \(23,\) you win \(\$ 350\) and also get back your \(\$ 10\) bet. If any other number comes up, you lose your \(\$ 10,\) or (2) Bet \(\$ 10\) on black. If the spin results in any one of the black numbers, you win \(\$ 10\) and also get back your \(\$ 10\) bet. If any other color comes up, you lose your \(\$ 10\). a. Without doing any calculation, which wager would you prefer? Explain why. (There is no correct answer. Peoples' choices are based on their individual preferences and risk tolerances.) b. Find the expected outcome for each wager. Which wager is better in this sense?

Short Answer

Expert verified
Bet 2 has a higher expected value, making it statistically better.

Step by step solution

01

Calculate the Probability of Winning with Bet 1

In Bet 1, you bet on a specific number, which is 23. Since there are 38 numbers available on the roulette wheel, the probability of the wheel landing on 23 is \(\frac{1}{38}\).
02

Calculate the Winnings and Loss for Bet 1

If the wheel lands on 23, you win \(\\(350\) and also receive your \(\\)10\) back, totaling \(\\(360\). If the wheel lands on any other number, you lose \(\\)10\).
03

Calculate the Expected Value for Bet 1

The expected value (EV) is calculated as: \[EV = (\text{Probability of winning}) \times (\text{Winnings}) + (\text{Probability of losing}) \times (\text{Loss})\]Plug in the values: \[EV = \frac{1}{38} \times 360 + \frac{37}{38} \times (-10)\]Calculate this to find the expected value for Bet 1.
04

Calculate the Probability of Winning with Bet 2

For Bet 2, you bet on black. There are 18 black numbers on the wheel, so the probability of winning this bet is \(\frac{18}{38}\).
05

Calculate the Winnings and Loss for Bet 2

If the ball lands on a black number, the outcome is \(\\(10\) in profit plus your original \(\\)10\) back, totaling \(\\(20\). If it does not land on a black number, you lose your entire \(\\)10\) bet.
06

Calculate the Expected Value for Bet 2

With the expected value formula:\[EV = (\text{Probability of winning}) \times (\text{Winnings}) + (\text{Probability of losing}) \times (\text{Loss})\]Plugging in the values:\[EV = \frac{18}{38} \times 20 + \frac{20}{38} \times (-10)\]Calculate this to find the expected value for Bet 2.
07

Compare Expected Values and Conclude

Compare the expected values from Bet 1 and Bet 2. A higher expected value indicates a better statistical outcome over a longer number of trials.

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Key Concepts

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

Expected Value
When we talk about Expected Value (EV), we are considering what you might gain or lose over many spins of the roulette. It gives you an average outcome, based on the probabilities. Let's take a closer look at how EV works in this exercise.
Bet 1 involves choosing a specific number, which is 23. If you win, you gain \(360 in total (\)350 plus your original \(10), but the chance of hitting that number is just \(\frac{1}{38}\). On the contrary, if any other number comes up, you lose your \)10. The EV for Bet 1 can be expressed as:
\[EV = \left(\frac{1}{38}\right) \times 360 + \left(\frac{37}{38}\right) \times (-10)\]
For Bet 2, you're wagering on the ball landing on a black number. The likelihood for this outcome is \(\frac{18}{38}\). Successful bets mean you earn \(20 in total (\)10 profit plus your \(10 back), or you lose your original \)10 if the ball doesn't land on black. Thus, the EV for Bet 2 is:
\[EV = \left(\frac{18}{38}\right) \times 20 + \left(\frac{20}{38}\right) \times (-10)\]
By examining these calculations, we can determine which bet statistically offers a better outcome over time by comparing their expected values.
Risk Assessment
Risk Assessment is determining what chance you are taking with a particular wager. Each bet offers different levels of risk and potential reward.
With Bet 1, there is a high risk because you're betting on a very unlikely event (only \(\frac{1}{38}\) probability of winning), but if it pays off, you earn a substantial amount (\(360). Essentially, you gamble on a single, more daring number, which offers high reward at a high risk.
On the other hand, Bet 2 is less risky due to the higher probability \(\frac{18}{38}\) that the ball will land on any of the black numbers. The reward here is smaller (a \)10 net gain), but so is the risk involved. This bet is more about incremental gains over a longer period compared to high stake scenarios like Bet 1.
Therefore, your assessment of each bet's risk can guide which wager might better suit your personal comfort levels and financial strategies. Some prefer the thrill of taking big chances with Bet 1, while others may lean toward steady wins with the lower risk of Bet 2.
Probability of Winning
Probability of Winning is simply the chance that a particular outcome will occur. Here, we look at how likely it is to win each bet based on the conditions given.
In Bet 1, the probability of landing on exactly the number 23 is \(\frac{1}{38}\). With only one winning number out of 38 possible outcomes on the roulette wheel, your chance of winning is pretty slim.
Conversely, Bet 2 offers a higher probability of winning. There are 18 black numbers, so the chances you pick any black number is \(\frac{18}{38}\). This means nearly half the time, you can expect to win if you bet on black.
Understanding these probabilities helps you make an informed decision. A higher probability sees a greater chance of frequent wins in the short term, whereas a lower probability might be riskier but could also provide higher rewards in a single lucky instance.

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Most popular questions from this chapter

{ For a normal }\end{array}\( distribution, a. Find the \)z\( -score for which a total probability of 0.02 falls more than \)z\( standard deviations (in either direction) from the mean, that is, below \)\mu-z \sigma\( or above \)\mu+z \sigma\( b. For this \)z\(, explain why the probability more than \)z\( standard deviations above the mean equals \)0.01 .\( c. Explain why \)\mu+2.33 \sigma$ is the 99 th percentile.

An exit poll is taken of 3000 voters in a statewide election. Let \(X\) denote the number who voted in favor of a special proposition designed to lower property taxes and raise the sales tax. Suppose that in the population, exactly \(50 \%\) voted for it. a. Explain why this scenario would seem to satisfy the three conditions needed to use the binomial distribution. Identify \(n\) and \(p\) for the binomial. b. Find the mean and standard deviation of the probability distribution of \(X\). c. Using the normal distribution approximation, give an interval in which you would expect \(X\) almost certainly to fall, if truly \(p=0.50\). (Hint: You can follow the reasoning of Example 14 on racial profiling.) d. Now, suppose that the exit poll had \(x=1706 .\) What would this suggest to you about the actual value of \(p ?\)

Jane Doe claims to possess extrasensory perception (ESP). She says she can guess more often than not the outcome of a flip of a balanced coin in another room. In an experiment, a coin is flipped three times. If she does not actually have ESP, find the probability distribution of the number of her correct guesses. a. Do this by constructing a sample space, finding the probability for each point, and using them to construct the probability distribution. b. Do this using the formula for the binomial distribution.

From past experience, a wheat farmer living in Manitoba, Canada finds that his annual profit (in Canadian dollars) is \(\$ 80,000\) if the summer weather is typical, \(\$ 50,000\) if the weather is unusually dry, and \(\$ 20,000\) if there is a severe storm that destroys much of his crop. Weather bureau records indicate that the probability is 0.70 of typical weather, 0.20 of unusually dry weather, and 0.10 of a severe storm. In the next year, let \(X\) be the farmer's profit. a. Construct a table with the probability distribution of \(X\). b. What is the probability that the profit is \(\$ 50,000\) or less? c. Find the mean of the probability distribution of \(X\). Interpret. d. Suppose the farmer buys insurance for \(\$ 3000\) that pays him \(\$ 20,000\) in the event of a severe storm that destroys much of the crop and pays nothing otherwise. Find the probability distribution of his profit.

A random number generator is used to generate a real number between 0 and 1 , equally likely to fall anywhere in this interval of values. (For instance, \(0.3794259832 \ldots\) is a possible outcome.) a. Sketch a curve of the probability distribution of this random variable, which is the continuous version of the uniform distribution (see Exercise 6.1). b. What is the mean of this probability distribution? c. Find the probability that this random variable falls between 0.25 and 0.75 .

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