Standardisation of normal variables: notes and practice questions
- Standardising converts a normal variable with mean and standard deviation to a standard normal variable :
- The standard normal distribution has mean 0 and standard deviation 1.
- Use standardisation to calculate probabilities using the standard normal table.
How it is examined
This is the subtopic where a probability is given and or is wanted: inverse normal for , then solve . Two unknowns needs two given probabilities and simultaneous equations, which is the harder version. Paper 2, 5 to 7 marks.
is given.
- Standardization of normal variables (-values).
- Inverse normal calculations where mean or standard deviation are unknown.
Linking questions
- Links to other subjects: the normal distribution (biology); descriptive statistics (psychology).
Practice questions
6 questions · 4 medium · 2 hardQuestion 1
MediumPaper 2 · calculator15 marksThe delivery times, minutes, for packages from a logistics hub to a regional distribution center can be modelled by a normal distribution with a mean of 120 minutes and a standard deviation of minutes.
Given that 3% of the delivery times are longer than 135 minutes, find the value of .
Find the probability that a randomly selected package will have a delivery time of more than 130 minutes.
Given that a package delivery takes longer than 130 minutes, find the probability that it takes less than 135 minutes.
On a particular day, there are 80 packages scheduled for delivery from the hub.
Find the expected number of packages that will have a delivery time of more than 130 minutes.
Find the probability that more than 8 of the packages on this particular day will have a delivery time of more than 130 minutes.
Use the inverse normal distribution function on your GDC to find the z-score corresponding to the given percentile. Remember that if 3% are longer than 135 minutes, then 97% are shorter than 135 minutes.
Use the normal cumulative distribution function (CDF) on your GDC. Remember to use the standard deviation found in part (a).
This is a conditional probability problem. Recall the formula . Here, event A is 'delivery takes less than 135 minutes' and event B is 'delivery takes longer than 130 minutes'.
This involves a binomial distribution. The expected value for a binomial distribution is given by , where is the number of trials and is the probability of success for a single trial (from part (b) ).
Use the binomial cumulative distribution function (CDF) on your GDC. Remember that 'more than 8' means , which can be calculated as .
Question 2
HardPaper 2 · calculator16 marks(a) The random variable follows a normal distribution with mean and standard deviation .
Find .
(b) The diameters of ball bearings produced by a factory, in mm, are normally distributed with mean and standard deviation . The ball bearings are categorized as defective, standard, large, or premium, according to their diameter. The following table shows the probability a ball bearing is classified into each category.
| Category | Probability |
|---|---|
| Defective | 0.03 |
| Standard | 0.65 |
| Large | 0.25 |
| Premium | 0.07 |
The maximum diameter of a defective ball bearing is 14.8 mm.
The minimum diameter of a premium ball bearing is 16.5 mm.
Find the value of and of .
(c) The factory rejects all defective ball bearings. The remaining ball bearings are sold.
Find the probability that a ball bearing chosen at random from those sold is categorized as
(i) standard;
(ii) large;
(iii) premium.
(d) The selling prices of the different categories of ball bearings at this factory are shown in the following table:
| Category | Selling Price ($) |
|---|---|
| Standard | 1.50 |
| Large | 1.80 |
| Premium | 2.50 |
The factory incurs a fixed cost of $300 for the production run and assumes it will sell the accepted ball bearings in exactly the same proportion as calculated in part (c).
According to this model, find the minimum number of accepted ball bearings that must be sold so that the net profit for the factory is at least $550.
Recall that for a normal distribution, you can standardize the variable to a standard normal variable using the formula . Then use your GDC to find the probability.
Use the given probabilities and boundary values to find the corresponding z-scores. Then, set up two simultaneous equations involving and and solve them.
This is a conditional probability problem. The new sample space consists only of non-defective ball bearings.
Remember to use the new sample space (non-defective ball bearings) for this conditional probability.
The denominator for the conditional probability remains the probability of a non-defective ball bearing.
First, calculate the expected revenue per accepted ball bearing using the probabilities from part (c) and the selling prices. Then, set up an inequality for the total profit.
Question 3
MediumPaper 2 · calculator15 marks(a) The lifespan of a new type of battery, hours, can be modelled by a normal distribution with a mean of 1200 hours and a standard deviation of hours.
Given that 5% of the batteries last longer than 1280 hours, find the value of .
(b) Find the probability that a randomly selected battery will have a lifespan of less than 1150 hours.
(c) Given that a battery lasts longer than 1150 hours, find the probability that it lasts less than 1250 hours.
(d) A batch of 500 batteries is produced. Find the expected number of batteries that will have a lifespan of less than 1150 hours.
(e) Find the probability that more than 85 of the batteries in this batch will have a lifespan of less than 1150 hours.
For part (a), use the inverse normal function on your GDC to find the z-score corresponding to the given percentile. Then, use the z-score formula to solve for . Remember that 5% lasting longer means 95% last less than that value.
For part (b), use the normal cumulative distribution function (CDF) on your GDC with the mean and standard deviation found in part (a). You need to find .
For part (c), this is a conditional probability problem. Recall the formula . Here, A is 'lasts less than 1250 hours' and B is 'lasts longer than 1150 hours'. So you need to find and .
For part (d), this involves a binomial distribution. The number of trials is the batch size, and the probability of success is the probability calculated in part (b). The expected number of successes in a binomial distribution is given by .
For part (e), you need to calculate for the binomial distribution . Remember that , and your GDC can compute using binomial CDF.
Question 4
HardPaper 2 · calculator7 marksThe masses of a certain type of melon are normally distributed with mean and standard deviation .
The probability that a randomly chosen melon has a mass greater than is .
If a melon with a mass greater than is chosen at random, the probability that its mass is greater than is .
Find the value of and the value of .
Use the conditional probability formula to find the overall probability that a melon has a mass greater than . Then, standardise both values to set up a system of two equations.
Question 5
MediumPaper 2 · calculator5 marks(a) The lifespan of a certain brand of LED bulbs, , is normally distributed with a mean of hours and a standard deviation of hours.
Find the probability that a randomly selected LED bulb lasts less than standard deviations below the mean lifespan.
(b) The manufacturer wants to determine a minimum lifespan threshold such that only of bulbs last longer than this threshold. Find the number of standard deviations, , above the mean that corresponds to this threshold.
For part (a), first determine the value that is standard deviations below the mean. Then, use the normal cumulative distribution function (CDF) to find the probability that is less than this value, or convert to a Z-score and use the standard normal distribution.
For part (b), you are given a probability and need to find a corresponding Z-score. Use the inverse normal distribution function (invNorm) to find the Z-score, , such that the probability of a bulb lasting more than standard deviations above the mean is . Remember that typically takes the cumulative probability from the left.
Question 6
MediumPaper 2 · calculator6 marksThe lifespan of a new model of LED light bulb, , is modelled by a normal distribution with mean hours and standard deviation hours.
It is observed that 15% of these bulbs fail before 8000 hours, and only 5% of the bulbs last longer than 12000 hours.
Find the value of and .
Use the inverse normal function to find the z-scores corresponding to the given probabilities. Then, set up and solve a system of two simultaneous equations.
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