Continuous Density and Distribution Functions
You get to a Metrobús stop where a bus comes by, without fail, every 5 minutes. You don't know when the last one left, so your wait could be any value between 0 and 5 minutes. What is the probability of waiting less than 2 minutes? You can't count cases one by one: there are infinitely many possible times. The answer will be an area.
The density function
When a random variable $X$ is continuous (time, height, weight), probability isn't split up among individual values. Instead we use a curve $f(x)$, the density function, and the probability of an interval is the area under the curve over that interval.
For the Metrobús stop, $f(x)=k$ between $0$ and $5$. The area is a rectangle with base $5$ and height $k$, and it must equal $1$: $5k=1$, so $k=0.2$.
The shaded area measures $2\times0.2=0.4$. Back to our opening question: the probability of waiting less than 2 minutes is $0.4$.
The density function of a continuous random variable $X$ is defined, representing the waiting time (in minutes) for a game to start on a video game server:…
The density function of a continuous random variable $X$ is defined, representing the waiting time (in minutes) for a game to start on a video game server:
$f(x) = \begin{cases} k & \text{if } 0 \le x \le 5 \\ 0 & \text{en el resto} \end{cases}$
- a) Determine the value of the constant $k$ so that $f(x)$ is a valid density function.
- b) Graph the function $f(x)$ using the value of $k$ you have obtained.
You can do it on paper and send a photo with your answer.
Given the following density function of a continuous random variable $X$, representing the waiting time in minutes in a fairground ride queue before getting on: $$f(x) =…
Given the following density function of a continuous random variable $X$, representing the waiting time in minutes in a fairground ride queue before getting on:
$$f(x) = \begin{cases} k & \text{if } 0 \le x \le 4 \\ 0 & \text{otherwise} \end{cases}$$Calculate the value of the constant $k$ so that the area under the function is equal to $1$ and graphically find the probability that a visitor waits less than $2$ minutes.
The battery life of a new wireless headphone model follows a uniform distribution between 4 and 10 hours. Its density function is constant in that interval:…
The battery life of a new wireless headphone model follows a uniform distribution between 4 and 10 hours. Its density function is constant in that interval: $f(x) = \frac{1}{6}$. Calculate the probability that the battery lasts between 5 and 8 hours, interpreting it as the area of a rectangle.
The distribution function
Calculating a new area every time is slow. The distribution function accumulates the area all at once.
When $f$ is defined piecewise, $F$ is too: on each piece it is the accumulated area, using whatever shape applies (rectangle, triangle, trapezoid).
Some densities are shaped like a trapezoid. You don't need the trapezoid formula: split it into a rectangle and a triangle, or use the complement.
The reaction time, in seconds, of a group of teenagers to a visual stimulus in a video game is being studied. The density function of this continuous variable is given…
The reaction time, in seconds, of a group of teenagers to a visual stimulus in a video game is being studied. The density function of this continuous variable is given by the following expression:
$f(x) = \begin{cases} kx & \text{if } 0 \le x \le 2 \\ 0 & \text{otherwise} \end{cases}$
Determine:
- a) The value of the constant $k$ so that $f(x)$ is a valid density function.
- b) The probability that a randomly chosen player has a reaction time greater than $1.5$ seconds.
- c) The probability that the reaction time is between exactly $0.5$ and $1$ seconds.
The waiting time, in minutes, for an update to download on a console follows a continuous distribution whose density function is in the shape of a trapezium. The…
The waiting time, in minutes, for an update to download on a console follows a continuous distribution whose density function is in the shape of a trapezium. The function is defined between $0$ and $10$ minutes. Between minutes $0$ and $4$, the function is constant with a value of $h$, and between minutes $4$ and $10$ it decreases linearly until reaching $0$.
- a) Calculate the value of $h$ so that it is a density function.
- b) Calculate the probability that the update takes less than $6$ minutes to download.
- c) If a user has been waiting for more than $4$ minutes, what is the probability that the download finishes before minute $8$?
Let $f(x)$ be a piecewise function defined as follows:…
Let $f(x)$ be a piecewise function defined as follows:
$f(x) = \begin{cases} k \times x & \text{if } 0 \le x < 2 \\ k \times (4 - x) & \text{if } 2 \le x \le 4 \\ 0 & \text{en el resto} \end{cases}$
- a) Determine, with justification, the value of the constant $k$ so that $f(x)$ is a density function of a continuous random variable $X$.
- b) Once $k$ has been found, calculate the probability that the variable takes a value in the interval $[1, 3]$, that is, $P(1 \le X \le 3)$.
- c) Graph the function $f(x)$ and shade in the drawing the area corresponding to the probability calculated in part b).
The median and conditional probability
For conditional probability we use $P(A\mid B)=\dfrac{P(A\cap B)}{P(B)}$. With the Metrobús stop: $P(X>3\mid X>1)=\dfrac{P(X>3)}{P(X>1)}=\dfrac{0.4}{0.8}=0.5$.
Given the density function $f(x) = \frac{1}{8}(x-1)$ defined for the interval $x \in [1, 5]$ and $f(x)=0$ elsewhere: a) Check that the total area under the curve is…
Given the density function $f(x) = \frac{1}{8}(x-1)$ defined for the interval $x \in [1, 5]$ and $f(x)=0$ elsewhere:
- a) Check that the total area under the curve is indeed $1$.
- b) Find a value $M$ (median) such that $P(X \le M) = 0.5$.
- c) Calculate the conditional probability $P(X > 4 | X > 2)$.
The standard normal curve
Many variables (height, grades, the weight of a product) have a bell-shaped density: the normal $N(\mu,\sigma)$, symmetric about its mean $\mu$. Its area can't be found with simple shapes, so we use a table for the standard normal $Z\sim N(0,1)$ (mean $0$, standard deviation $1$).
The table gives $F(z)=P(Z\le z)$, the accumulated area to the left of $z$. You look up the units digit and the first decimal in the row, and the second decimal in the column.
Some table values: $P(Z\le0)=0.5$, $P(Z\le1)=0.8413$, $P(Z\le1.5)=0.9332$, $P(Z\le1.96)=0.9750$, $P(Z\le2)=0.9772$.
Given a standard normal distribution $Z \sim N(0, 1)$, use the probability table to find the following values directly: a) $P(Z \le 0.45)$ b) $P(Z \le 1.2)$ c)…
Given a standard normal distribution $Z \sim N(0, 1)$, use the probability table to find the following values directly:
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a) $P(Z \le 0.45)$
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b) $P(Z \le 1.2)$
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c) $P(Z \le 2.38)$
For a variable $Z \sim N(0, 1)$, apply the properties of the normal curve (symmetry and total area) to calculate the following probabilities: a) $P(Z > 1.52)$ b)…
For a variable $Z \sim N(0, 1)$, apply the properties of the normal curve (symmetry and total area) to calculate the following probabilities:
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a) $P(Z > 1.52)$
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b) $P(Z < -0.84)$
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c) $P(Z \ge -1.15)$
Given a random variable $Z$ following a standard normal distribution $N(0, 1)$, use symmetry properties and the total area to calculate the following probabilities: a)…
Given a random variable $Z$ following a standard normal distribution $N(0, 1)$, use symmetry properties and the total area to calculate the following probabilities:
- a) $P(Z < 1.42)$
- b) $P(Z > -0.75)$
- c) $P(1.12 < Z < 2.05)$
- d) $P(-1.5 < Z < 1.5)$
- e) Find the value of $k$ such that $P(Z < k) = 0.8830$
Intervals and the table in reverse
For an interval, you subtract two table values. For example, $P(0.62\le Z\le1.96)=F(1.96)-F(0.62)$.
You can also use the table backwards: you're given the probability and you look for $z$. You find the value closest to the probability inside the table and read $z$ from its row and column.
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$P(Z\le k)=0.8413\Rightarrow k=1$.
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$P(Z\le k)=0.9750\Rightarrow k=1.96$.
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$P(Z\le k)=0.5\Rightarrow k=0$.
If the given probability is less than $0.5$, then $z$ is negative: look up the complement and change the sign.
Calculate the probability that the standard normal variable $Z$ takes a value lying in the interval $(0.62 \le Z \le 1.96)$. Remember that to calculate the area of an…
Calculate the probability that the standard normal variable $Z$ takes a value lying in the interval $(0.62 \le Z \le 1.96)$. Remember that to calculate the area of an interval, you must subtract the cumulative areas: $P(a \le Z \le b) = P(Z \le b) - P(Z \le a)$.
Use the $N(0, 1)$ distribution table in reverse to find the value of the constant $k$ in the following cases: a) $P(Z \le k) = 0.8413$ b) $P(Z \le k) = 0.9750$ c)…
Use the $N(0, 1)$ distribution table in reverse to find the value of the constant $k$ in the following cases:
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a) $P(Z \le k) = 0.8413$
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b) $P(Z \le k) = 0.9750$
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c) $P(Z \le k) = 0.5000$
Standardizing any normal
The table is only for $N(0,1)$. For a normal $X\sim N(\mu,\sigma)$ we standardize: we measure how many standard deviations $x$ is from the mean.
If you're asked how many items to expect, multiply the probability by the total: with $500$ orders and $P=0.0668$, we expect $500\times0.0668=33.4$, about $33$.
The scores on an English placement test for Sixth Form students follow a normal distribution with a mean of $\mu = 75$ and a standard deviation of $\sigma = 8$.…
The scores on an English placement test for Sixth Form students follow a normal distribution with a mean of $\mu = 75$ and a standard deviation of $\sigma = 8$. Standardise the following values of variable $X$ to find their corresponding value in $Z$:
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a) A score of $83$.
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b) A score of $67$.
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c) A score of $75$.
The weight of bags of chips produced by a machine follows a distribution $N(150, 5)$ grams. Calculate the probability that a randomly chosen bag weighs less than $160$…
The weight of bags of chips produced by a machine follows a distribution $N(150, 5)$ grams. Calculate the probability that a randomly chosen bag weighs less than $160$ grams. To do this, standardize the variable first and look up the result in the table.
The heights of 11th-grade students in a city follow a normal distribution with a mean of $170$ cm and a standard deviation of $8$ cm. a) What percentage of students are…
The heights of 11th-grade students in a city follow a normal distribution with a mean of $170$ cm and a standard deviation of $8$ cm.
- a) What percentage of students are between $162$ and $178$ cm tall?
- b) If a sports team selection requires a minimum height of $154$ cm, what is the probability that a randomly chosen student does not meet this requirement?
- c) What is the probability that a student is taller than $180$ cm?
Cutoff values and unknown parameters
There are two types of inverse problems:
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Cutoff value (for example, "the top $5\,\%$"): you look up $z$ in the table and solve for $x=\mu+z\sigma$.
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Unknown parameters: each piece of information of the form "$x\,\%$ falls below such-and-such a value" gives a $z$ and therefore an equation $\mu+z\sigma=\text{value}$. With two pieces of information, you solve a system of two equations.
A courier company has analysed the weight of the packages it sends daily. It has been shown that the weight follows a normal distribution. We know that $15.87 \%$ of the…
A courier company has analysed the weight of the packages it sends daily. It has been shown that the weight follows a normal distribution. We know that $15.87 \%$ of the packages weigh less than $2$ kg and that $2.28 \%$ of the packages weigh more than $8$ kg.
- a) Determine the mean and standard deviation of the weight of the packages.
- b) What is the probability that a randomly chosen package weighs between $3$ and $6$ kg?
The daily usage time of a map app on the cell phones of delivery drivers in a city follows a normal distribution $N(\mu, \sigma)$. It is known that $15.87 \%$ of drivers…
The daily usage time of a map app on the cell phones of delivery drivers in a city follows a normal distribution $N(\mu, \sigma)$. It is known that $15.87 \%$ of drivers use it for less than $40$ minutes a day, while $2.28 \%$ use it for more than $80$ minutes. Calculate the parameters $\mu$ and $\sigma$ of this distribution. What is the probability that a randomly chosen driver uses the app for between $50$ and $70$ minutes?
In a young musical talent competition, the scores follow a normal distribution with a mean of $72$ points. It is known that to obtain an "Honourable Mention", a score is…
In a young musical talent competition, the scores follow a normal distribution with a mean of $72$ points. It is known that to obtain an "Honourable Mention", a score is required such that only $10 \%$ of participants achieve it. If the minimum score to receive this mention is $84.8$ points, what is the standard deviation of the scores? If $500$ participants enter, how many are expected to have a score below $60$ points?
From the binomial to the normal
If $X\sim B(n,p)$ with $n$ large, calculating $P(X=k)$ one by one is tedious. We can approximate it with a normal distribution.
An electronic component manufacturing company claims that $4 \%$ of its touchscreens have some factory micro-defect. If a school purchases a batch of $250$ screens for…
An electronic component manufacturing company claims that $4 \%$ of its touchscreens have some factory micro-defect. If a school purchases a batch of $250$ screens for its classrooms, calculate the probability that:
- a) There are exactly $12$ defective screens.
- b) There are between $8$ and $15$ defective screens (inclusive).
Note: Justify whether it is possible to approximate the binomial distribution to the normal distribution and apply Yates' continuity correction.