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In other words "our society has modified and tempered with traditional values and beliefs for their own selfish wants" to me this quote seems like a negative view, not one the speaker is enthusiastic about. He/she is not pleased with the way the "world has skewed values"
But hey as with many forms of literature, especially quotes they can be interpreted many different ways so read more than one response. Hope this helped
What else can I help you with?
When the majority of the data values fall to the right of the mean the distribution is said to be left skewed?
When the majority of the data values fall to the right of the mean, the distribution is indeed said to be left skewed, or negatively skewed. In this type of distribution, the tail on the left side is longer or fatter, indicating that there are a few lower values pulling the mean down. This results in the mean being less than the median, as the median is less affected by extreme values. Overall, left skewed distributions show that most data points are higher than the average.
What direction does the tail face in a positively skewed and what direction in a negatively skewed set of data?
In a positively skewed distribution, the tail faces to the right, indicating that there are a few exceptionally high values pulling the mean upwards. Conversely, in a negatively skewed distribution, the tail faces to the left, reflecting the presence of a few exceptionally low values that pull the mean downwards. This skewness affects the relationship between the mean, median, and mode in each case.
In general the distribution of F-ratios is?
positively skewed with all values greater than or equal to zero
When a curve is pulled upward by extreme high scores is it skewed positive?
Yes, when a curve is pulled upward by extreme high scores, it is said to be positively skewed. In a positively skewed distribution, the tail on the right side is longer or fatter, indicating that there are a few unusually high values that affect the overall shape of the distribution. This results in the mean being greater than the median.
When the mean and median do not coincide?
When the mean and median do not coincide, it typically indicates that the data distribution is skewed. In a positively skewed distribution, the mean is greater than the median, while in a negatively skewed distribution, the mean is less than the median. This discrepancy arises because the mean is sensitive to extreme values, whereas the median is resistant to outliers, making it a better measure of central tendency in skewed distributions. Understanding this difference helps in accurately interpreting the data's characteristics.
How do you spell skewed as in not correct?
The word is correctly spelled "skewed" meaning distorted or out of line, as with numerical values or sequences. The similar word is askew.
What is A set of data values called where there are more data values above the Mean?
skewed
When the majority of the data values fall to the right of the mean the distribution is said to be left skewed?
When the majority of the data values fall to the right of the mean, the distribution is indeed said to be left skewed, or negatively skewed. In this type of distribution, the tail on the left side is longer or fatter, indicating that there are a few lower values pulling the mean down. This results in the mean being less than the median, as the median is less affected by extreme values. Overall, left skewed distributions show that most data points are higher than the average.
What direction does the tail face in a positively skewed and what direction in a negatively skewed set of data?
In a positively skewed distribution, the tail faces to the right, indicating that there are a few exceptionally high values pulling the mean upwards. Conversely, in a negatively skewed distribution, the tail faces to the left, reflecting the presence of a few exceptionally low values that pull the mean downwards. This skewness affects the relationship between the mean, median, and mode in each case.
In general the distribution of F-ratios is?
positively skewed with all values greater than or equal to zero
What type of distribution pattern that occurs when the majority of the data values fall to the left of the mean?
positively skewed
What distinguishes a normal curve from a skewed curve?
A normal curve, also known as a bell curve, is symmetric around its mean, indicating that data points are evenly distributed on either side, with most values clustering around the center. In contrast, a skewed curve is asymmetrical, meaning that it has a tail extending more to one side than the other; in a positively skewed curve, the tail is on the right, while in a negatively skewed curve, it is on the left. This skewness affects the mean, median, and mode of the data distribution, leading to different interpretations of the data's central tendency.
What can lead to skewed perceptions of the world.?
Logical Fallacies
If a great many data values cluster to the left of a data distribution which then tails off to the right the distribution is referred to as?
It is a positively skewed distribution.
When a curve is pulled upward by extreme high scores is it skewed positive?
Yes, when a curve is pulled upward by extreme high scores, it is said to be positively skewed. In a positively skewed distribution, the tail on the right side is longer or fatter, indicating that there are a few unusually high values that affect the overall shape of the distribution. This results in the mean being greater than the median.
When the mean and median do not coincide?
When the mean and median do not coincide, it typically indicates that the data distribution is skewed. In a positively skewed distribution, the mean is greater than the median, while in a negatively skewed distribution, the mean is less than the median. This discrepancy arises because the mean is sensitive to extreme values, whereas the median is resistant to outliers, making it a better measure of central tendency in skewed distributions. Understanding this difference helps in accurately interpreting the data's characteristics.
Is considerably skewed distribution the same as bimodal distribution?
No. A distribution may be non-skewed and bimodal or skewed and bimodal. Bimodal means that the distribution has two modes, or two local maxima on the curve. Visually, one can see two peaks on the distribution curve. Mixture problems (combination of two random variables with different modes) can produce bimodal curves. See: http://en.wikipedia.org/wiki/Bimodal_distribution A distribution is skewed when the mean and median are different values. A distribution is negatively skewed when the mean is less than the median and positively skewed if the mean is greater than the median. See: http://en.wikipedia.org/wiki/Skewness
