The mean must be 0 and the standard deviation must be 1.
Use the formula: z = (x - mu)/sigma
I believe your question is to find a range going from the mean to a z-value on the standard normal distribution that corresponds to 17% of the area. A normal distribution goes from values of minus infinity to positive infinity. A standard normal distribution has a mean of 0 and an standard deviation of 1. It is usually best if you draw a diagram, in this case a bell shape curve with mean = 0. The area to the left of the mean is 50% of the total area. We find a z value that corresponds to 67% (50% + 17%) of the area to the left of this value. This can be done either with a lookup table or a spreadsheet program. I prefer excel, +norminv(0.67) = 0.44. The problem could also be worded to find the area going from a z-value to the mean. In this case, we must find a z-value that corrsponds to 33% (50-17). Using Excel, I calculate +norminv(0.33) = -0.44.
Nothing needs to be done. Normal is considered anything from 90 to 110.
Nothing in particular. It has its normal dictionary definition. All kinds of conversion can be done in mathematics.
A value that is obtained from calculations and assuming the project or experiment had no energy was lost in the system to the surrounding and done under standard conditions.
To write 6200 in standard form, you would simply write it as it is: 6200. In standard form, numbers are written in a way that is easy to read and understand, with each digit representing a specific place value. In this case, the number 6200 is already in standard form because it is written using the standard base-ten numeration system.
There are no benefits in doing something that cannot be done. The standard normal distribution is not transformed to the standard distribution because the latter does not exist.
The z-score table is the cumulative distribution for the Standard Normal Distribution. In real life very many random variables can be modelled, at least approximately, by the Normal (or Gaussian) distribution. It will have its own mean and variance but the Z transform converts it into a standard Normal distribution (mean = 0, variance = 1). The Z-distribution is then used to make statistical inferences about the data. However, there is no simple analytical method to calculate the values of the distribution function. So, it has been done and tabulated for easy reference.
I believe your question is to find a range going from the mean to a z-value on the standard normal distribution that corresponds to 17% of the area. A normal distribution goes from values of minus infinity to positive infinity. A standard normal distribution has a mean of 0 and an standard deviation of 1. It is usually best if you draw a diagram, in this case a bell shape curve with mean = 0. The area to the left of the mean is 50% of the total area. We find a z value that corresponds to 67% (50% + 17%) of the area to the left of this value. This can be done either with a lookup table or a spreadsheet program. I prefer excel, +norminv(0.67) = 0.44. The problem could also be worded to find the area going from a z-value to the mean. In this case, we must find a z-value that corrsponds to 33% (50-17). Using Excel, I calculate +norminv(0.33) = -0.44.
The derivation of an individual consumer demand curve can be done using the indifference curve approach. This is done by preparing the demand schedule of a consumer from the price consumption curve.
The quincunx method is a statistical technique used to generate random numbers that follow a normal distribution. It involves dropping balls onto a series of pins arranged in a quincunx pattern, and the final distribution of the balls at the bottom follows a bell-shaped curve similar to a normal distribution. It is often used in the teaching of statistics to demonstrate the central limit theorem.
Curving a grade involves adjusting scores to account for the difficulty of an exam or assignment. This is typically done by shifting the overall score distribution to better reflect the performance of students.
Advanced users are the typical users with more technical knowledge. Standard users are the normal ones who uses computers to just get the task done.
The Bezier curve is the standard curve type used in most graphics software. It is unusual in that it has no more than four points (as opposed to other kinds of curves, which can have many points): two endpoints and up to two control points. The position of the control points determines the shape of the curve. The Bezier curve can also curve back upon itself, which many other computer graphics curves can't. The Bezier curve was patented by Pierre Bezier, an engineer at Renault. The first project ever done using Bezier curves was the Renault Le Car.
To curve a test effectively, you can adjust the scores based on the overall performance of the students. This can help account for any unusually difficult questions or ensure that the grading accurately reflects the students' understanding of the material. Curving can be done by adjusting the raw scores to a standard distribution or by setting a minimum passing score. It is important to consider the test's difficulty and the students' performance to ensure fair grading and accurate assessment of their abilities.
Cotton production and distribution in India before the industrial revolution was done in large-scale.
A curved grade in academic assessment signifies that the scores of students are adjusted to fit a predetermined distribution, typically a bell curve. This is done to ensure fairness and consistency in grading across different sections or years.
Yes, work done in a reversible process can be calculated using the area under the curve on a PV diagram. This is because the work done is equal to the area enclosed by the process curve on a PV diagram.