z = 0.5244, approx.
Answer: 0 The z score is the value of the random variable associated with the standardized normal distribution (mean = 0, standard deviation =1). Now, the median and the mean of a normal distribution are the same. The 50 percentile z score = the median = mean = 0.
Provided the distribution is Normal, the z-score is the value such that the probability of observing a smaller value is 0.25. Thus z = -0.67449
You will need to use tables of z-score or a z-score calculator. You cannot derive the value analytically.The required z-score is 0.524401
Normal distribution is a perfectly symmetrical bell-shaped normal distribution. The bell curve is used to find the median, mean and mode of a function.
Each standard deviation represents a certain percentile. So if we use two decimal places, −3 is the 0.13th percentile, −2 the 2.28th percentile, −1 the 15.87th percentile, 0 the 50th percentile , +1 the 84.13th percentile, +2 the 97.72th percentile, and +3 the 99.87th percentile.The mean, median and mode are all the same it the distribution is normal.BUT WHY DOES THIS WORK? HOW DO YOU DO IT?The main idea to make all this work and understandable is that the area under the normal curve is one. So if you have a SD and a mean, you can find the z score.Then, using a calculator, or a table, or even sometimes just some rules you may have learned like the empirical rule, you can find the area to the left or right of any given z score. This area is actually a percentile!So for example, if convert a data point to a z - score using the mean and standard deviation ( The formula is z=(x-mean)/standard deviation, by the way), and I look up the probability of that z-score, and say it is .25. Then it is the 25th percentile.The table below gives you all the percentiles and their corresponding z scores.z-score percentile for normal distributionPercentilez-ScorePercentilez-ScorePercentilez-Score1-2.32634-0.412670.442-2.05435-0.385680.4683-1.88136-0.358690.4964-1.75137-0.332700.5245-1.64538-0.305710.5536-1.55539-0.279720.5837-1.47640-0.253730.6138-1.40541-0.228740.6439-1.34142-0.202750.67410-1.28243-0.176760.70611-1.22744-0.151770.73912-1.17545-0.126780.77213-1.12646-0.1790.80614-1.0847-0.075800.84215-1.03648-0.05810.87816-0.99449-0.025820.91517-0.954500830.95418-0.915510.025840.99419-0.878520.05851.03620-0.842530.075861.0821-0.806540.1871.12622-0.772550.126881.17523-0.739560.151891.22724-0.706570.176901.28225-0.674580.202911.34126-0.643590.228921.40527-0.613600.253931.47628-0.583610.279941.55529-0.553620.305951.64530-0.524630.332961.75131-0.496640.358971.88132-0.468650.385982.05433-0.44660.412992.326
it doesn't exist.
Answer: 0 The z score is the value of the random variable associated with the standardized normal distribution (mean = 0, standard deviation =1). Now, the median and the mean of a normal distribution are the same. The 50 percentile z score = the median = mean = 0.
To find what z-score represents the 80th percentile, simply solve for 0.8 = F(z), where F(x) is the standard normal cumulative distribution function. Solving gives us: z = 0.842
No. It is not apparent what 0.2422 refers to.
75th percentile
Z Score is (x-mu)/sigma. The Z-Score allows you to go to a standard normal distribution chart and to determine probabilities or numerical values.
Provided the distribution is Normal, the z-score is the value such that the probability of observing a smaller value is 0.25. Thus z = -0.67449
If you have a variable X that is normally distributed with mean m and variance s2 then the z-score, Z = (X - m)/s.Z has a standard Normal distribution.
A researcher wants to go from a normal distribution to a standard normal distribution because the latter allows him/her to make the correspondence between the area and the probability. Though events in the real world rarely follow a standard normal distribution, z-scores are convenient calculations of area that can be used with any/all normal distributions. Meaning: once a researcher has translated raw data into a standard normal distribution (z-score), he/she can then find its associated probability.
To convert your 1979 ACT score to percentile scores, you can reference historical data from the ACT organization, which provides percentile ranks for various scores. You may need to find a specific ACT score percentile table from that year, as percentiles can change annually based on the performance of test-takers. Alternatively, tools or resources that aggregate historical ACT data can help you identify the corresponding percentile for your score. If you cannot find specific data from 1979, you might consider using more recent percentile data as a general guide, keeping in mind that it may not be perfectly accurate for that year.
Z = -0.8416
You can't do this without knowing the distribution of scores.