Mean is the arithmetic average of a distribution, obtained by adding the scores and then dividing it by the number of scores there are. Median is the middle score in a distribution; half the scores are above it and half the scores are below it. Mode is the most frequently occurring score in a distribution. A skewed distribution is when the distribution is leaning toward one side. It is the measure asymmetric probability and its real value of data. A skewed would be like a group of random people who take an IQ test all score above average would be skewed upwards. The three measures of central tendency, mean, median, and mode, would all be in the same place, the center of a distribution, on a normal distribution. In a positively skewed distribution the measures of central tendency will not be in the same place, they would be above the average, median, score.

In an intelligence test where the mean is 100 and the standard deviation is 15 are distributed in a certain way. Standard deviation is a computed measure of how the scores vary around the mean score. This means that 100 is the average score of all the scores and the scores vary about 15 points around the mean score.

If there are two groups, group one with a mean of 100 and group two with a mean of 115, there can be a higher score in group one than the mean of group two. A score in group one can be higher than 115 so long as it contributes to the average score of 100.

Norms for intelligence tests are periodically updated because more people have taken the test thereby updating the measures of central tendencies.
An intelligence test is bias when the questions are geared toward a particular subject and not all areas of intelligence. It can also be bias if the test is administered differently to different people.

...What are the characteristics of a population for which a mean/median/mode would be appropriate? Inappropriate?
The analysis of data begins with descriptive statistics such as the mean, median, mode, range, standard deviation, variance, standard error of the mean, and confidence intervals. These statistics are used to summarize data and provide information about the sample from which the data were drawn and the accuracy with which the sample represents the population of interest. The mean, median, and mode are measurements of the “central tendency” of the data. The range, standard deviation, variance, standard error of the mean, and confidence intervals provide information about the “dispersion” or variability of the data about the measurements of central tendency.
MEASUREMENTS OF CENTRAL TENDENCY The appropriateness of using the mean, median, or mode in data analysis is dependent upon the nature of the data set and its distribution (normal vs non-normal). The mean (denoted by x) is calculated by dividing the sum of the individual data points (where Σ equals “sum of”) by the number of observations (denoted by n). It is the arithmetic average of the observations and is used to describe the center of a data set.
mean=x= One of the most basic purposes of statistics is simply to enable us to make sense of large numbers. For example, if you want to know how the students in your school are doing in the statewide achievement...

...Descriptive Statistics: Real Estate
University of Phoenix
RES/341 Research and Evaluation I
Descriptive Statistics: Real Estate
Does having a pool increase the price of houses that have the same number of bedroom? In order to answer that question, we divided our data set into two groups; houses with 1 to 3 bedrooms and houses with 4 and more bedrooms. We then compared the prices of houses with a pool to houses without a pool in each group. Different calculations were used to determine the central tendency, dispersion, and the skew of our data. The central tendency helps to simplify data and also to predict future results. We can use diverse calculations to measure it such as the mean, mode, and median. According to our sample of houses with 1 to 3 bedrooms, the mean price was higher of $4,060 for houses without a pool than with a pool. The same rule applies to houses with more than 4 bedrooms, but with a larger difference of $51,170. Another way we used to calculate the central tendency is by finding the median. The medians are also higher in each group for houses without a pool than those with a pool.
To better answer the above question, we also analyzed the skewness of our data in the two groups. . If we look at the two groups, houses with 1 to 3 bedrooms and houses with 4 or more bedrooms, the data seems to be skewed to the right because the mean is larger than the median. However, due to the small difference between the...

...Descriptive Statistics paper
RES/341
July 24, 2011
Descriptive Statistics paper
The information below is a continuance of week two, week three, and on week four. The previous assessment in week two on “real estate research” for thinking of hypothesis on home values in Alvarado, Texas. The evaluating on real estate prices reveals a purpose of this research paper and its importance findings. The discoveries include problem definition, and on variables.
The next assessment was on week three on “data collection” on reviewing literatures, sampling design, and on any ethical concerns with collection data on the same topic. A summary was assembled in week three on terms of population, sampling size, and factors on real estate. This research found house prices to change in each different region.
This is week four paper on “descriptive statistics” on real estate in Alvarado, Texas. The information below will consist of; data analysis, data using graphic and tabular techniques, and on skew values, histogram measures, and on central tendency.
The Central tendency is the measures of numerical summaries used to summarize data with a one number. The most common used are mode, mean, and median. The Hypothesis is "homes more or less expensive fifteen miles away from the center of the city"? The comparison will come from the City of Arlington, Texas, and Cedar Hill. The mode is the data that happens most frequently in the data...

...
Name
Assignment
QNT/561
Date
Descriptive Statistics
Sales (in USD)
The distribution is normally distributed.
Central Tendency:
Mean = 42.84 dollars.
Dispersion:
Standard deviation = 9.073 dollars.
Count:
100
Min/Max:
Min is $23.00; Max is $64.00
Confidence Interval (alpha = 0.05):
$41.06 to $44.62
The histogram is present in Appendix A; the descriptive statistics are present in Appendix B.
Age
The distribution is not normally distributed.
Central Tendency:
Median = 35 years
Dispersion:
Interquartile Range = 12 years / 2 = ± 6 years
Count:
100
Min/Max:
Min is 25 years; Max is 45 years
Confidence Interval:
The data is not normally distributed, therefore there is no confidence interval
The histogram is present in Appendix A; the descriptive statistics are present in Appendix B; the scatterplot relating age and sales is in Appendix C.
ID On Display
Thirty-four percent of the people sampled did not have their ID on display while sixty-six percent of people sampled had their ID on display. The bar chart is in Appendix E.
Descriptive Statistics Interpretation
Sales
One hundred people were randomly selected, and their sales were measured. Their sales were observed between $23.00 and $64.00. The average sales were $42.84, with a standard deviation of $9.07. Approximately half or more of the data values are above $42.84. There is enough evidence to say that the population sales amount lies...

...Business Statistics MFM I Semester
I.Chakrapani Asst. Professor – FMS NIFT, Hyderabad
Course Objectives
To understand the fundamentals of statistics and its application in the field of fashion industry To familiarise the students with SPSS for data feeding, processing, analysis and interpretation Analyse data quantitatively to interpret an existing situation/problem with the help of SPSS
Course Contents
Session 1 Introduction tostatistics – What & Why Scope of statistics and its applications in marketing & managerial decision making Collection, classification and presentation of data
Course Contents Session 2 Measures of central tendency & Dispersion Mean, Median, Mode Range, Mean deviation & standard deviation
Course Contents Session 3 Probability Distributions Normal distribution Sampling distribution Session 4 Chi - Square Chi - Square as a test of independence
Course Contents
Session 5 Estimation, Confidence intervals Testing of hypothesis for simple mean proportions (large and small samples) Difference between means and proportions Z test T test
Course Contents Session 6 Correlation Scatter diagram Karl Pearson’s coefficient of correlation Spearman’s rank Correlation coefficient
Course contents
Session 7 Linear Regression analysis & Forecasting Simple bivariate regression analysis (y = a +bx types) Time series analysis Moving averages Methods of least square
Course contents...

...Charismatic Condition
Mean 4.204081633
Standard Error 0.097501055
Median 4.2
Mode 4.8
Standard Deviation 0.682507382
Sample Variance 0.465816327
Kurtosis 5.335286065
Skewness -1.916441174
Range 3.5
Minimum 1.5
Maximum 5
Sum 206
Count 49
Confidence Level(95.0%) 0.196039006
In both the Charismatic and the punitive condition data sets there were 49 people surveyed. We know this because we were able to use descriptive statistics to show the count and that shows the number of people surveyed. The average or the mean of the charismatic condition is 4.20. The standard error is saying that 0.0975 % is the error that will normally occur if two different people are comparing results. The middle value or the median of the data set is 4.2 and the most frequently occurring value or mode is 4.8. The charismatic condition is skewed to the left because we are getting a negative number for the skewness data. The skewness is at -1.916441174. The difference between the largest and the smallest value which is also called the range is 3.5. The minimum score is 1.5 and the maximum score was a 5 given by the students for the charismatic condition.
The Frequency for the charismatic condition is telling us the summary of the data that is presented is the form of class intervals and frequency. This bar graph will show you the values of the scores starting at 1.5 and going up to 5. The frequency shows us the number of students who picked the...

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D. The river/lake where a fish was captured
4. Managers study the number of days per month over the last year that employees in the payroll department called in sick to determine the averages they can expect next year. Collecting the data and determining the averages last year is an example of what type of statistics? Determining the averages they can expect next year is an example of what type of statistics?
A. They are both examples of inferential statistics because averages are inferred in both instances.
B. Inferential statistics; descriptive statistics.
C. They are both examples of descriptive statistics because they deal with analyzing data.
D. Descriptive statistics; inferential statistics.
5. The grades that a random sampling of students in the psychology degree program received over the last decade of "Abnormal Psychology" classes are an example of what statistical concept?
A. The grades are an example of a parameter.
B. The grades are an example of a sample.
C. The grades are an example of a population.
D. The grades are an example of a statistic.
6. What method is used to sample a population so that it is representative of the population?
A. All but the samples that appear to have the lowest and highest values are selected.
B. Samples are chosen at random from the...

...LEAD 6341
Research Methods and Statistics
Midterm Exam
Part I: Calculations (Open Book)
Spring, 2013
Note: For the following computational exercises, show all steps of your work (when appropriate). Do NOT simply put an answer. Show or explain how you arrived at your answer.
1) Compute the mean, median, and mode for the following distribution: (5 pts)
1,2,2,3,3,3,3,3,3,4,4,5,6,7,7,8,8,8,8,8,8,9,9,10
The mean is what people call the average. (1+2+2+3+3+3+3+3+3+4+4+5+6+7+7+8+8+8+8+8+8+9+9+10 = 127/24 = 5.2916
Mean = 5.29
The median is the middle value. When the middle does not fall neatly in the distribution, use the following formula to identify the position. In the formula n is the sample size.
Median position = (n + 1) / 2
Median position = (24 + 1)/2
Median position = 25/2 = 12.5
Now we look for position 12 and 13. Position 12 is 5, and position 13 is 6. We take the average of the two values and that is the median. Median = (5 + 6)/2 = 11/2 = 5.5
Median = 5.5
The mode is the most frequent response in the distribution
1 – 1 6 – 1
2 – 2 7 – 2
3 – 6 8 – 6
4 – 2 9 – 2
5 – 1 10 – 1
In this example we have two modes. They are 3 and 8.
2) You have been asked to give a student two different tests; an intelligence test and a creativity test. The student scored 123 on the intelligence test and 123 on the creativity test. The mean for the intelligence test is 100, and the standard...