Statistics in Intelligence Testing Essay
Statistics are often used to describe and interpret the results of intelligence testing.
After gathering data using descriptive, correlation, or experimental research methods, we organize, summarize, and make inferences from that data using statistics.
To summarize the data, we use the three measures of central tendency: The simplest measure is the mode, the most frequently occurring score. The most common reported is the mean, or arithmetic average (the total sum of all the scores divided by the number of scores. The median is the middle score or the 50th percentile. These measures of central tendency can be inaccurate when there is a skewed distribution, a few atypical scores that distort the results. For example, if 75 percent of the testers scored less than the mean score, then 25 percent of the scores were high enough to cause the mean to inflate, which proves it is the most biased by a few extreme scores.
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In a normal distribution, the measures of central tendency help describe and interpret the results of intelligence testing in an accurate manner. The normal distribution of data has no atypical scores, which can lead to the mean, median, or mode being biased. These atypical scored could be caused by many variables in the experiment, such as, age, race, sex, or level of education. In a positively skewed distribution, the results of the testing tend to favor the positive factor in the experiment. The presenter may show the data in a way that favors the result or might cause us to misinterpret the data. By better understanding the measures of central tendency and how it is presented, we will better understand data shown to us.
In an intelligence test where the scores are normally distributed as a mean of 100 and the standard deviation is 15, the scores are distributed in an unbiased way. If the standard deviation is only 15, the scores are approximately between 85-115. Using the mean of 100 is an accurate way to present the data.
In two normal distributions, if group I has a mean of 100 and group II has a mean of 115, an individual in group I may have a higher score that the mean score for group II. This can happen if there are lower scores in group I, which would bring the group mean down and allow for few higher scores to be above 115.
Statistics are often used to describe and interpret the results of intelligence testing and can be manipulated be the presenter. We must understand how the data is presented to avoid being misled.
After gathering data using descriptive, correlation, or experimental research methods, we organize, summarize, and make inferences from that data using statistics.
To summarize the data, we use the three measures of central tendency: The simplest measure is the mode, the most frequently occurring score. The most common reported is the mean, or arithmetic average (the total sum of all the scores divided by the number of scores. The median is the middle score or the 50th percentile. These measures of central tendency can be inaccurate when there is a skewed distribution, a few atypical scores that distort the results. For example, if 75 percent of the testers scored less than the mean score, then 25 percent of the scores were high enough to cause the mean to inflate, which proves it is the most biased by a few extreme scores.
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In a normal distribution, the measures of central tendency help describe and interpret the results of intelligence testing in an accurate manner. The normal distribution of data has no atypical scores, which can lead to the mean, median, or mode being biased. These atypical scored could be caused by many variables in the experiment, such as, age, race, sex, or level of education. In a positively skewed distribution, the results of the testing tend to favor the positive factor in the experiment. The presenter may show the data in a way that favors the result or might cause us to misinterpret the data. By better understanding the measures of central tendency and how it is presented, we will better understand data shown to us.
In an intelligence test where the scores are normally distributed as a mean of 100 and the standard deviation is 15, the scores are distributed in an unbiased way. If the standard deviation is only 15, the scores are approximately between 85-115. Using the mean of 100 is an accurate way to present the data.
In two normal distributions, if group I has a mean of 100 and group II has a mean of 115, an individual in group I may have a higher score that the mean score for group II. This can happen if there are lower scores in group I, which would bring the group mean down and allow for few higher scores to be above 115.
Statistics are often used to describe and interpret the results of intelligence testing and can be manipulated be the presenter. We must understand how the data is presented to avoid being misled.
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