Find the z-score for an IQ test score of 118 when the mean is 100 and the standard deviation is 15

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Find the z-score for an IQ test score of 92 when- the mean is 100 and the standard deviation is 15_

Z-score, otherwise known as the standard score, is the number of standard deviations by which a data point is above the mean. You can use our z-score calculator to determine this value for you. Read on to learn how to calculate the z-score and how to use the z-score table.

Z-score is a value used to describe the normal distribution. It is defined as the distance between the mean score and the experimental data point, expressed in terms of SD (standard deviation). In statistical data analysis, it is also called standard score, z value, standardized score and normal score.

To find the z-score, you first need to calculate the mean and standard deviation of a data set. Mean, denoted with the symbol μ, is the sum of all values in the data set, divided by the number of data points. It can be written down as μ = ∑x / n. Standard deviation is found according to the expression

σ = √[∑(x - μ)² / n]

where x stands for raw value, and n for the number of data points.

To find the z-score, you simply need to apply the following formula:

z = (x - μ) / σ

Let's assume a following task: during a test, four students scored 50, 53, 62 and 70 points. What is the z-score of the result 62?

1. Find the mean of the results. μ = (50 + 53 + 62 + 70) / 4 = 58.75. You can also use our average calculator to do it.
2. Calculate the individual values of (x - μ)² for each result:

• (50 - 58.75)² = 76.5625
• (53 - 58.75)² = 33.0625
• (62 - 58.75)² = 10.5625
• (70 - 58.75)² = 126.5625

1. Calculate the standard deviation: √[(76.5625 + 33.0625 + 10.5625 + 126.5625) / 4] =√(246.75 / 4) = 7.854
2. Input these results to the z-score equation for x = 62: z = (62 - 58.75) / 7.854 = 0.41.
3. You just found the z-score of 62! You can also use the z-score calculator to find the mean or standard deviation if you know the z-score.

A z-score table is where you can find the area to the left of the given z-score under the standard distribution graph. The first column of the table is a list of z-values (accurate to one decimal place). In the first row, you can find the digit that is on the second decimal place of your z-score.

For example, we found the z-score of 62 in our example to be equal to 0.41. First, you need to find z = 0.4 in the first column; this value shows you in which row you need to seek. Then, find the value of 0.01 in the first row. It will determine the row in which you must look. The area under the standard distribution graph (to the left of our z-score) is equal to 0.6591. Remember that the total area under this graph is equal to 1. Hence, we can say that the probability of a student scoring 62 or lower on the test is equal to 0.6591, or 65.91%.

Knowing this area, you can also find the p-value - probability that the score will be higher than 62. It is simply 1 - 0.6591 = 0.3409, or 34.09%.

99.7% of observation of a process that follows the normal distribution can be found either to the right or to the left from the distribution mean. Hence, only 0.03% of all the possible realizations of this process will lay outside of the three sigma interval.

If you try to expand this interval and go six sigmas to left and right, you will find out that 99.9999998027% of your data points fall into this principles. If this principle is successfully applied you can expect to have 3.4 defects for every one million realizations of a process.

Such events may be considered as very unlikely: accidents and mishaps, on the one hand, and streaks of luck, on the other. If you perform a repetitive task that can be described by the normal distribution (such as a production of a standardized good), in the long run you may expect serious errors to happen so rarely that they become negligible.

This is the reason behind the quality control system based on the standard normal distribution, called the six sigma. Engineered at Motorola in the 1980s the system uses statistical analysis to measure end eliminate errors.

There are five main elements to this process: a) define, b) measure, c) analyze, d) improve, and e) control. The basic notion is that a process requires a serious correction when it deviates more than three sigma from its mean. In other words, the main objective of your quality management and controls should be to have your production process outcome as close to the normal distribution as possible.

Because of the six sigma methodology, in the last three decades the normal distribution has been used to enhance processes from manufacturing to transactions, both in factories and offices.

The z-score tells you how many standard deviations a data point is above or below the mean. A positive z-score means the data point is greater than the mean, while a negative z-score means that it is less than the mean. A z-score of 1 means that the data point is exactly 1 standard deviation above the mean.

To find the z-score on a regular calculator, follow these steps:

1. Calculate the mean as (∑x) / n.
2. Calculate the standard deviation using the easy-to-type formula (∑(x²) - (∑x)²/n) / n. The divisor is modified to n - 1 for sample data.
3. Calculate the z-score using the formula z = (x - mean) / standard deviation.

Yes, a negative z-score indicates that your data point is lower than the mean!

A z-score table helps you find the p-value, or percentile, your data point corresponds to based on its z-score. Follow these steps:

1. Determine if your z-score is negative or positive.
2. If the z-score is negative (i.e., the data point is less than the mean), use a negative z-score table. If the z-score is positive (i.e., the data point is greater than the mean), use a positive z-score table.
3. Look in the leftmost column to find the z-score that matches yours up to the first decimal (10th place). E.g., for a z-score of 2.15, find 2.1.
4. Look in the top row to find the z-score which matches the second decimal (100th place). E.g., for a z-score of 2.15, find 0.05.
5. Find the p-value where the matching row and column intersect. For a z-score of 2.15, the z-score table gives you a p-value of 0.98422.
6. To find percentile, multiply the p-value by 100%. A z-score of 2.15 is in the 98th percentile.

A z-score of 1.645 indicates that your data point is in the 95th percentile.

If you know the mean and standard deviation, you can find z-score using the formula z = (x - μ) / σ where x is your data point, μ is the mean, and σ is the standard deviation.

The easiest way to find p-value from z-score is to use a z-score table. The actual calculation involves integrating the area under the curve of a normal distribution.