Last updated on June 12th, 2025
The Z-score table is an usual, mathematical table that helps you find the probability of a data point appearing in a normal distribution. It gets the job done by converting values into standard deviations and revealing how far the data point is from the average or the mean. We use the Z score table to analyze data by comparing data points and calculating probabilities. It is useful to convert Z scores into probabilities. In this topic, we will discuss Z score table and its applications.
Z table or the standard normal distribution table is a mathematical chart used to represent the percentage of values that are less than a particular z score value. There can be two types of z score tables, depending on the values, a positive table and a negative table. Z score tables are useful because they can help us calculate the probability of a data point appearing in a normal distribution.
There are countless normal distributions and it is difficult to print each distribution. Hence, we convert a normal to a standard normal distribution, which is known as the Z score table. Then use the Z-score table to find the probabilities.
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Z score table can only be used when we know the value of z. The value represents a number to indicate how many standard deviations the value is below or above the mean. Z score can be used to calculate both sample and population data.
By using the given formulas, z score is calculated:
For population data: z = (x - μ) / π
Here, x is the raw score
μ is the population mean
π is the standard deviation of a population
Next, for sample data: z = (x - xΜ) / s
Here,
xΜ = sample mean
s = sample standard deviation
x = raw score
Take a look at this example,
If the class average on a science test is 60 with a standard deviation of 10, students who scored 80 can. Let’s say a class is averaging 60 on a recently concluded examination, with a standard deviation of 10. Then, the students averaging 80 can calculate their Z score as follows:
Here, the standard deviation (x) = 80
The mean (μ) = 60
the population standard deviation (π) = 10
By using the formula of Z score: z = (x - μ) / π
z = (80 - 60) / 10 = 2
z = 2
Thus, the student’s science score is 2 standard deviations above the class average.
The Z score table is divided into two types, negative and positive z score tables. A negative z score means the data point of the random variable is below the mean.
A positive z score means the value is above the mean. We should use the negative z score table to find the values below the mean. Likewise, we use a positive z score table to find the values that fall above the mean or less than the positive z score. The cells in the table describe the area and the rows and columns represent the z score. Here are the negative and positive z score tables, take a look at this:
There are certain steps that should be followed while using a Z score table. The steps are listed below:
Step 1: The first step is to determine the z score for the said data point. Then, we should find the mean and standard deviation. The z score explains how far the data point is from the average or mean.
Step 2: Analyze the Z score table. The left side column represents the Z scores. The matching percentiles or probabilities are on the table’s body.
Step 3: Identifying the z score, located on the left-most column of the table, is the next step. If we do not find the exact z score, estimate the probability by interpolating between the nearest values.
Let us understand this with an example,
In a university, the average score of an entrance exam has a mean of 70 and a standard deviation of 10. One of the students wants to find the probability of scoring below 85.
Solution:
First, we need to calculate the Z score.
z = (x - μ) / π
z = 85 - 70 / 10
z = 15 / 10 = 1.5
Now, from the z score table, we should identify the cumulative probability corresponding to 1.5. The probability for z = 1.5 is 0.9332.
0.9332 × 100 = 93.32%
The probability of the student scoring below 85 is 93.32%.
In statistics, mathematics, and research Z score is a vital tool to find the probabilities of values. It makes the calculation and analysis of data much easier for students.
Misunderstanding the concepts of the Z score table can lead to incorrect probability calculations. The Z score is a fundamental aspect of statistics and mathematics. It helps students to calculate the probabilities in a normal distribution. Some of the common mistakes and its helpful solutions are given below:
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Joe took a math test where the class average was 75 with a standard deviation of 5. He scored 80. Joe wants to know how well he performed compared to his classmates.
Better than 84.13% of his classmates.
To calculate the Z score, we can use the formula:
z = (x - μ) / π
Here, x = 80
μ = 75
π = 5
Now, we can substitute the values:
z = (80 - 75) / 5
z = 5 / 5 = 1.0
So, the cumulative probability for z = 1.0 is 0.8413
It means Joe performed better than 84.13% of his classmates.
Sam is 7 feet tall. The average height for men in his college is 6.5 feet with a standard deviation of 0.5 feet. Sam wonders how much taller he is compared to the average man.
Sam is taller than 84.13% of the men in his college.
x = 7 feet
μ = 6.5 feet
π = 0.5 feet
The Z score formula is:
z = (x - μ) / π
z = (7 - 6.5) / 0.5
z = 0.5 / 0.5 = 1
Here, the cumulative probability of 1 is 0.8413.
Sam is taller than approximately 84.13% of the men in his college.
In a school, the average weight of students is 30 kg with a standard deviation of 25 kg. A student has 40 kg. Is this student heavier than most?
Yes, the student is heavier than most.
The formula for the Z score is:
z = (x - μ) / π
Where, x = 40
μ = 30
π = 25
z = 40 - 30 / 25
z = 10 / 25 = 0.4
The Z score of 0.4 corresponds to 0.6554.
So, more than half of the students (65.54%) weigh less than this student.
If x is 50, the mean (ΞΌ) is 40, and the standard deviation (π) is 5. What is the Z score?
2.0
Here, x = 50
μ = 40
π = 5
The formula is: z = (x - μ) / π
Now, we can substitute the values.
z = 50 - 40 / 5
z = 10 / 5 = 2
The Z score is 2.0, which means, the value 50 is 2 standard deviations above the mean.
What is the probability that a Z score lies between -2.00 and 2.00?
0.9544 or 95.44%
Here, we need to find the cumulative probability for z = -2.00 and z = 2.00. From the Z score table, we find that the probability of z = -2.00 is 0.0228
The probability for z = 2.00 is 0.9772
Next, we have to subtract the lower from the higher probability.
0.9772 - 0.0228 = 0.9544
To convert the number to percentage, we have to multiply it by 100:
0.9544 × 100 = 95.44%
So, the probability that a Z score lies between -2.00 and 2.00 is 0.9544 or 95.44%.
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Jaipreet Kour Wazir is a data wizard with over 5 years of expertise in simplifying complex data concepts. From crunching numbers to crafting insightful visualizations, she turns raw data into compelling stories. Her journey from analytics to education ref
: She compares datasets to puzzle gamesβthe more you play with them, the clearer the picture becomes!