This document discusses key concepts about the normal distribution and z-scores, including:
- Approximately 68%, 95%, and 99% of scores in a normal distribution fall within 1, 2, and 3 standard deviations of the mean, respectively.
- A z-score describes how many standard deviations a raw score is above or below the mean, and allows comparison of scores from different distributions.
- The normal curve table lists percentages of scores associated with different z-scores and can be used to find percentages of scores above or below a given value.
Understanding the Z- score (Application on evaluating a Learner`s performance)Lawrence Avillano
Application of Z-score or standard score on evaluating a students performance. It includes the formula for z-value, interpretation of in relation to the mean and stdev, sample step by step calculation and interpretationof z-score, and sample real scenario application.
In statistics, the standard score is the (signed) number of standard deviations an observation or datum is above the mean. Thus, a positive standard score represents a datum above the mean, while a negative standard score represents a datum below the mean. It is a dimensionless quantity obtained by subtracting the population mean from an individual raw score and then dividing the difference by the population standard deviation. This conversion process is called standardizing or normalizing (however, "normalizing" can refer to many types of ratios; see normalization (statistics) for more).Standard scores are also called z-values, z-scores, normal scores, and standardized variables; the use of "Z" is because the normal distribution is also known as the "Z distribution". They are most frequently used to compare a sample to a standard normal deviate (standard normal distribution, with μ = 0 and σ = 1), though they can be defined without assumptions of normality.
Understanding the Z- score (Application on evaluating a Learner`s performance)Lawrence Avillano
Application of Z-score or standard score on evaluating a students performance. It includes the formula for z-value, interpretation of in relation to the mean and stdev, sample step by step calculation and interpretationof z-score, and sample real scenario application.
In statistics, the standard score is the (signed) number of standard deviations an observation or datum is above the mean. Thus, a positive standard score represents a datum above the mean, while a negative standard score represents a datum below the mean. It is a dimensionless quantity obtained by subtracting the population mean from an individual raw score and then dividing the difference by the population standard deviation. This conversion process is called standardizing or normalizing (however, "normalizing" can refer to many types of ratios; see normalization (statistics) for more).Standard scores are also called z-values, z-scores, normal scores, and standardized variables; the use of "Z" is because the normal distribution is also known as the "Z distribution". They are most frequently used to compare a sample to a standard normal deviate (standard normal distribution, with μ = 0 and σ = 1), though they can be defined without assumptions of normality.
Measurement errors, Statistical Analysis, UncertaintyDr Naim R Kidwai
The Presentation covers Measurement Errors and types, Gross error, systematic error, absolute error and relative error, accuracy, precision, resolution and significant figures, Measurement error combination, basics of statistical analysis, uncertainty, Gaussian Curve, Meaning of Ranges
O Z Scores 68 O The Normal Curve 73 O Sample and Popul.docxhopeaustin33688
O Z Scores 68
O The Normal Curve 73
O Sample and Population 83
O Probability 88
O Controversies: Is the Normal Curve
Really So Normal? and Using
Nonrandom Samples 93
• Z Scores, Normal Curves, Samples
and Populations, and Probabilities
in Research Articles 95
O Advanced Topic: Probability Rules
and Conditional Probabilities 96
O Summary 97
• Key Terms 98
O Example Worked-Out Problems 99
O Practice Problems 102
O Using SPSS 105
O Chapter Notes 106
CHAPTER 3
Some Key Ingredients
for Inferential Statistics
Z Scores, the Normal Curve, Sample
versus Population, and Probability
Chapter Outline
IMETII'M'Ir919W1191.7P9MTIPlw
0 rdinarily, psychologists conduct research to test a theoretical principle or the effectiveness of a practical procedure. For example, a psychophysiologist might measure changes in heart rate from before to after solving a difficult problem.
The measurements are then used to test a theory predicting that heart rate should change
following successful problem solving. An applied social psychologist might examine
Before beginning this chapter, be
sure you have mastered the mater-
ial in Chapter 1 on the shapes of
distributions and the material in
Chapter 2 on the mean and stan-
dard deviation.
67
68 Chapter 3
Z score number of standard deviations
that a score is above (or below, if it is
negative) the mean of its distribution; it
is thus an ordinary score transformed so
that it better describes the score's location
in a distribution.
the effectiveness of a program of neighborhood meetings intended to promote water
conservation. Such studies are carried out with a particular group of research partici-
pants. But researchers use inferential statistics to make more general conclusions about
the theoretical principle or procedure being studied. These conclusions go beyond the
particular group of research participants studied.
This chapter and Chapters 4, 5, and 6 introduce inferential statistics. In this
chapter, we consider four topics: Z scores, the normal curve, sample versus popula-
tion, and probability. This chapter prepares the way for the next ones, which are
more demanding conceptually.
Z Scores
In Chapter 2, you learned how to describe a group of scores in terms and the mean
and variation around the mean. In this section you learn how to describe a particular
score in terms of where it fits into the overall group of scores. That is, you learn how
to use the mean and standard deviation to create a Z score; a Z score describes a score
in terms of how much it is above or below the average.
Suppose you are told that a student, Jerome, is asked the question, "To what extent
are you a morning person?" Jerome responds with a 5 on a 7-point scale, where 1 =
not at all and 7 = extremely. Now suppose that we do not know anything about how
other students answer this question. In this situation, it is hard to tell whether Jerome is
more or less of a m.
Variability, the normal distribution and converted scoresNema Grace Medillo
Understanding mean and standard deviation in the normal distribution curve, Understanding scores using range, semi-interquartile range, standard deviation and variance. Converting scores through z- scores and t - scores,
1242019 Z Score Table - Z Table and Z score calculationw.docxaulasnilda
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Z Table
Find values on the left of the mean in this negative Z score
table. Table entries for z represent the area under the bell curve to
the left of z. Negative scores in the z-table correspond to the values
which are less than the mean.
Z S C O R E TA B L E
http://www.z-table.com/
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Z S C O R E TA B L E
http://www.z-table.com/
https://www.weebly.com/signup?utm_source=internal&utm_medium=footer
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Find values on the right of the mean in this z-table. Table entries for z
represent the area under the bell curve to the left of z. Positive
scores in the Z-table correspond to the values which are greater
than the mean.
Z S C O R E TA B L E
http://www.z-table.com/
https://www.weebly.com/signup?utm_source=internal&utm_medium=footer
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Z S C O R E TA B L E
http://www.z-table.com/
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Z Score Calculation and Z Table Application Example
Here is an example of how a z-score applies to a real life situation and how it can be calculated using a z-table.
Imagine a group of 200 applicants who took a math test. George was among the test takers and he got 700 points
(X) out of 1000. The average score was 600 (µ) and the standard deviation was 150 (σ). Now we would like to
know how well George performed compared to his peers.
We need to standardize his score (i.e. calculate a z-score corresponding to his actual test score) and use a z-table
to determine how well he did on the test relative to his peers. In order to derive the z-score we need to use the
following formula:
Therefore: Z score = (700-600) / 150 = 0.67
Now, in order to figure out how well George did on the test we need to determine the percentage of his peers
who go higher and lower scores. That’s where z-table (i.e. standard normal distribution table) comes handy. If
you noticed there are two z-tables with negative and positive values. If a z-score calculation yields a negative
standardized score refer to the 1st table, when positive used the 2nd table. For George’s example we need to use
the 2nd table as his test result corresponds to a positive z-score of 0.67.
Finding a corresponding probability is fairly easy. Find the first two digits on the y axis (0.6 in our example).
Z S C O R E TA B L E
http://www.z-table.com/
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Then go to the x axis to find the second decimal number (0.07 in this case). The nu ...
Work hard to make certain that the results you have are accurate b.docxkeilenettie
Work hard to make certain that the results you have are accurate based on class material.
Use T- table and Z-table when needed.
Feel free to consult and cite the notes and previous assignments in preparing this exam.
Please show all of your working out so I am able to see your path to your answer. Mistakes will be penalized however showing your working out will allow me to deduct fewer points. If no working out is shown, I will be forced to deduct full points for mistakes.
**
.
Z table and T table are attached.
Please read carefully
!
When appropriate and possible, express your answer in the same units as the variable.
For example, if the question asks for the mean years of formal education and you have calculated the mean to be 18.44, your answer should be expressed as “
18.44 years of formal education
.”
Equations to Use
Median Position = N+1/2
The
Median Value
is the midpoint between the scores.
Mean
=
å
x
/ N
Standard Deviation =
Z score =
x – mean / standard deviation
CI =
For samples sizes ≥ 100,
the formula for the
CI
is:
CI
=
(the sample mean) + & - Z(
s / √N – 1)
CI =
For samples sizes < 100,
the formula for the
CI
is:
CI
=
(the sample mean) + & - T(
s / √N – 1)
Please answer the following questions:
You are interested in the effects of release with aftercare for a small number of drug offenders. The number of additional months without drug use for a sample
of 6 offenders
is recorded. The data on the six (6) subjects are as follows:
2
8
5
2
8
2
What are the
median position
and the
median value
?
(3 points)
What is the mean?
(
2 points)
What is the most frequently occurring score in this distribution of scores - mode?
(2 point)
2. Computation of a mode is most appropriate when a variable is measured at which level?
(2 points)
A. interval-ratio
B. ordinal
C. nominal
D. discrete
Answer: ________________________
3.
Assume that the distribution of a college entrance exam is normal with
a mean of 500 and a standard deviation of 100
.
For each score below, find the equivalent Z score, the percentage of the area above the score, and the percentage of the area below the score.
( 5 each = total 10 points)
Score Z score % Area Above % Area Below
a) 437
b) 526
4. The class intervals below represent ages of respondents. Which list is both exhaustive and mutually exclusive?
(2 points)
A. 119–120, 120–121, 121–122
B. 119–120, 121–122, 123–124
C. 119–121, 123–125, 127–129
D. 119–120, 122–123, 125–126
Answer: ______________________
5. The parole board is alarmed by the low number of years actually spent in prison for those inmates sentences to 15-year sentences. To help them make parole recommendations they gather data on the number of years served for a small sample of 7 (
seven) p
otential parolees. The number of years served for these seven parol.
3. The normal distribution and standard deviations Mean -1 +1 In a normal distribution: Approximately 68% of scores will fall within one standard deviation of the mean
4. The normal distribution and standard deviations Mean +1 -1 +2 -2 In a normal distribution: Approximately 95% of scores will fall within two standard deviations of the mean
5. The normal distribution and standard deviations Mean +2 +1 -1 -2 +3 -3 In a normal distribution: Approximately 99% of scores will fall within three standard deviations of the mean
7. Using standard deviation units to describe individual scores Here is a distribution with a mean of 100 and and standard deviation of 10: 100 110 120 90 80 -1 sd 1 sd 2 sd -2 sd What score is one sd below the mean? 90 120 What score is two sd above the mean?
8. Using standard deviation units to describe individual scores Here is a distribution with a mean of 100 and and standard deviation of 10: 100 110 120 90 80 -1 sd 1 sd 2 sd -2 sd 1 How many standard deviations below the mean is a score of 90? How many standard deviations above the mean is a score of 120? 2
9. Z scores z scores are sometimes called standard scores Here is the formula for a z score: A z score is a raw score expressed in standard deviation units. What is a z-score?
10. z-score describes the location of the raw score in terms of distance from the mean, measured in standard deviations Gives us information about the location of that score relative to the “average” deviation of all scores A z-score is the number of standard deviations a score is above or below the mean of the scores in a distribution. A raw score is a regular score before it has been converted into a Z score. Raw scores on very different variables can be converted into Z scores and directly compared. What does a z-score tell us?
11. Mean of zero Zero distance from the mean Standard deviation of 1 The z-score has two parts: The number The sign Negative z-scores aren’t bad Z-score distribution always has same shape as raw score Z-score Distribution
12. z = (X –M)/SD Score minus the mean divided by the standard deviation Computational Formula
13. Jacob spoke to other children 8 times in an hour, the mean number of times children speak is 12, and the standard deviation is 4, (example from text). To change a raw score to a Z score: Step One: Determine the deviation score. Subtract the mean from the raw score. 8 – 12 = -4 Step Two: Determine the Z score. Divide the deviation score by the standard deviation. -4 / 4 = -1 Steps for Calculating a z-score
14. Using z scores to compare two raw scores from different distributions You score 80/100 on a statistics test and your friend also scores 80/100 on their test in another section. Hey congratulations you friend says—we are both doing equally well in statistics. What do you need to know if the two scores are equivalent? the mean? What if the mean of both tests was 75? You also need to know the standard deviation What would you say about the two test scores if the SDin your class was 5 and the SDin your friend’s class is 10?
15. Calculating z scores What is the z score for your test: raw score = 80; mean = 75, SD= 5? What is the z score of your friend’s test: raw score = 80; mean = 75, S = 10? Who do you think did better on their test? Why do you think this?
16. Transforming scores in order to make comparisons, especially when using different scales Gives information about the relative standing of a score in relation to the characteristics of the sample or population Location relative to mean Relative frequency and percentile Why z-scores?
17.
18. Figure the deviation score. Multiply the Z score by the standard deviation. Figure the raw score. Add the mean to the deviation score. Formula for changing a Z score to a raw score: X= (Z)(SD)+M Computing Raw Score from a z-score
19. Standardizes different scores Example in text: Statistics versus English test performance Can plot different distributions on same graph increased height reflects larger N Comparing Different Variables
20. How Are You Doing? How would you change a raw score to a Z score? If you had a group of scores where M = 15 and SD = 3, what would the raw score be if you had a Z score of 5?
21. Normal Distribution histogram or frequency distribution that is a unimodal, symmetrical, and bell-shaped Researchers compare the distributions of their variables to see if they approximately follow the normal curve.
22. Use to determine the relative frequency of z-scores and raw scores Proportion of the area under the curve is the relative frequency of the z-score Rarely have z-scores greater than 3 (.26% of scores above 3, 99.74% between +/- 3) The Standard Normal Curve
23. Why the Normal Curve Is Commonly Found in Nature A person’s ratings on a variable or performance on a task is influenced by a number of random factors at each point in time. These factors can make a person rate things like stress levels or mood as higher or lower than they actually are, or can make a person perform better or worse than they usually would. Most of these positive and negative influences on performance or ratings cancel each other out. Most scores will fall toward the middle, with few very low scores and few very high scores. This results in an approximately normal distribution (unimodal, symmetrical, and bell-shaped).
24. The Normal Curve Table and Z Scores A normal curve table shows the percentages of scores associated with the normal curve. The first column of this table lists the Z score The second column is labeled “% Mean to Z” and gives the percentage of scores between the mean and that Z score. The third column is labeled “% in Tail.” .
26. Using the Normal Curve Table to Figure a Percentage of Scores Above or Below a Raw Score If you are beginning with a raw score, first change it to a Z Score. Z = (X – M) / SD Draw a picture of the normal curve, decide where the Z score falls on it, and shade in the area for which you are finding the percentage. Make a rough estimate of the shaded area’s percentage based on the 50%–34%–14% percentages. Find the exact percentages using the normal curve table. Look up the Z score in the “Z” column of the table. Find the percentage in the “% Mean to Z” column or the “% in Tail” column. If the Z score is negative and you need to find the percentage of scores above this score, or if the Z score is positive and you need to find the percentage of scores below this score, you will need to add 50% to the percentage from the table. Check that your exact percentage is within the range of your rough estimate.