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Standard deviation is the spread of the data. If each score has 7 added, this would not affect the spread of the data - it would be just as evenly spaced or clumped up, but 7 greater. The only thing that would affect the spread is multiplying every data point by 0.9. This makes distances between the data points 0.9 times as big, and thus makes the standard deviation 0.9 times as big. The standard deviation was 5.6, and so now is 5.6x0.9 = 5.04
The expected rate of return is simply the average rate of return. The standard deviation does not directly affect the expected rate of return, only the reliability of that estimate.
Outliers are observations that are unusually large or unusually small. There is no universally agreed definition but values smaller than Q1 - 1.5*IQR or larger than Q3 + 1.5IQR are normally considered outliers. Q1 and Q3 are the lower and upper quartiles and Q3-Q1 is the inter quartile range, IQR. Outliers distort the mean but cannot affect the median. If it distorts the median, then most of the data are rubbish and the data set should be examined thoroughly. Outliers will distort measures of dispersion, and higher moments, such as the variance, standard deviation, skewness, kurtosis etc but again, will not affect the IQR except in very extreme conditions.
It depends on what the standard deviation for that particular scale is. The most well-known scales have standard deviations of 15. In that case, 145 is three standard deviations above the average. People with this score are considered borderline geniuses. You can expect a well-educated student who has this IQ to be about six, maybe seven years ahead of his classmates. Someone with this IQ is incredibly intelligent and creative. Creativity, in this sense, is not artistic talent. It is the ability to solve logical problems using previously unknown methods. For example, someone who creates a new way to solve sudoku problems is intelligent, not someone who learns how to use them. One in 741 people reach the fourth standard deviation (an IQ of 145 or above in this case). IQ does not measure academic skill. It measures academic potential. The IQ test on tickle.com should be thought of as an aptitude test. Tests that measure actual IQ have questions similar to those on iqtest.dk. Even the WISC and WAIS IQ tests have questions which should only be put in aptitude tests. Remember that no matter which test it is, an online test is invalid. Even if it's a well made, properly calibrated test, your surroundings can affect your score.
Yes.
This would increase the mean by 6 points but would not change the standard deviation.
this dick
Standard deviation is the spread of the data. If each score has 7 added, this would not affect the spread of the data - it would be just as evenly spaced or clumped up, but 7 greater. The only thing that would affect the spread is multiplying every data point by 0.9. This makes distances between the data points 0.9 times as big, and thus makes the standard deviation 0.9 times as big. The standard deviation was 5.6, and so now is 5.6x0.9 = 5.04
The expected rate of return is simply the average rate of return. The standard deviation does not directly affect the expected rate of return, only the reliability of that estimate.
Yes. The standard deviation and mean would be less. How much less would depend on the sample size, the distribution that the sample was taken from (parent distribution) and the parameters of the parent distribution. The affect on the sampling distribution of the mean and standard deviation could easily be identified by Monte Carlo simulation.
Trends, covariance, and correlation are the big ones. Statistical significance, unit roots, heteroskedasticity, and format and source of the data would affect quality too.
Some data in statistics can affect numbers, which will skew the data. When this happens managers should make business decisions that ignore the stats.
No, and no. Think about two skewed distributions that are mirrored across the mean so that one is right and one is left. they have the same mean and standard deviation, but are opposite. Also, the 5 number summary does not affect a histogram
The estimated standard deviation goes down as the sample size increases. Also, the degrees of freedom increase and, as they increase, the t-distribution gets closer to the Normal distribution.
Variables that affect power in a statistical test include the sample size (larger sample sizes increase power), the effect size (larger effect sizes increase power), the significance level (higher significance levels increase power), and the variability in the data (less variability can increase power). Additionally, the chosen statistical test and the presence of confounding variables can also impact the power of a study.
The characters affect.