Means
The dependent variable was defined as how people rated themselves when presented with, “I am good at managing unpredictable situations.” The scale was numbered 1-5, 5 meaning strong agreement and 1 meaning strong disagreement. The overall mean of the dependent variable was a 3.46. This places the mean above the neutral point and indicates that the group was in a slight agreement with the statement. The mean of the group that had none to few restrictions was a 3.57. In relation to the scale of measurement, this group was somewhat in agreement with the statement. This was also the highest mean of the predictor variables. This group agreed most that they are with the statement. The Several restrictions group had a mean of 3.48. This
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They had the largest standard deviation of the group at 1.075. This means that on average, the data points in that group fell about 1.075 above or below the mean, making a larger span of the data. All of the groups were below the gold standard 50% or less than the mean for having outliers. However, the group that was closest to having minor outliers was the many retractions group. The standard deviation was 33% of the mean, the highest out of the other categories. The some restrictions group that was farthest away from having minor outliers with a standard deviation of 26.6% of the mean. The lowest percent of the groups.
Estimating with SDs and SEs
When evaluating standard error scores of the dependent variable the range was between 3.393 and 3.525. When evaluating the range from the standard deviation the range was between 2.503 and 4.414. The standard error provided a stronger degree of precision when evaluating the mean than the standard deviation because the standard error had a smaller range of scores than the standard deviation. If these were population statistics, then the minimum score needed to be equal to or greater than 1.548. This score is the second standard deviation below the mean, scores lower than this would mean that it is significant. On the higher end, scores must be equal to or below 5.370. This score is the second standard deviation above the mean, scores above this number would also result in significant data. If someone
Standard deviation is a way of visualizing how spread out points of data are in a set. Using standard deviation helps to determine how rare or common an occurrence is. For example, data points falling within the boundaries of one standard deviation typically account for about 68% of data and those between (+/-)1 standard deviation and (+/-)2 standard deviations make about 27% combined. This can be better visualized by using a bell graph. Using the mean and standard deviation, the points where standard deviations occur can be drawn on the graph to better understand which data is rare and which is common.
Standard deviation is important in comparing two different sets of data that has the same mean score. One standard deviation may be small (1.85), where the other standard deviation score could be quite large (10)(Rumsey,
Theoretically from the recorded data the calculated mean, median, and mode will be the most accurate representation of the real world value. The difference between the highest recorded value and lowest recorded value is the range in the set of data. Standard deviation (s) is a quantity calculated to indicate an extend of deviation for a group of data as a whole (Marshall). This is calculated using:
Standard Deviation of Mean= 0.4762Standard Deviation of Median= 0.7539The standard deviation of the Mean is smaller, which means all of the data points will tend to be very close to the Mean. The Median with a larger Standard Deviation will tend to have data points spread out over a large range of values. Since the Mean has the smaller value of the Standard Deviations, it has the least variability.
Standard Deviation for the mean column is 0.476Standard Deviation for the median column is 0.754Standard deviation for the mean column has least variability
Dunbar, G. (2005). Evaluating Research Methods in Psychology. New Jersey: John Wiley & Sons Inc.
8. Analyze: How does the standard deviation relate to the consistency and range of a data set?
| | B | Std. Error | Beta | | | 1 | (Constant) | 1.892 | .077 | | 24.606 | .000 | | Need for Achievement | .512 | .021 | .570 | 24.319 | .000 | | Cognitive Ability | .092 | .015 | .145 | 6.185 | .000 | a. Dependent Variable: Job Performance | 局部中介。 、显著性检验: Sobel test: a=0.052 sa=0.021 b=0.512 sb=0.021
The following Probability Plot clearly exposes any outliers; data entries that are . . . “far removed from the other entries the data set”, (Larson & Farber, 2011. pg. 68). We can see from this plot that there are several outliers on the high and low end of the data. However, one outlier in particular could cause the conclusions made about the data to be flawed. The data point located at 98%, 4600, is of major concern, as it is causing this set of data to appear much higher. It is recommended that this entry be ignored when making conclusions about the data set as a whole.
The last variable chose was number of prior drug convictions. The mean was .33 the median was 0 and the mode was 0. The mode is the most appropriate measure for this set of data because 957 people have had 0 prior drug convictions out of 1160. The next closest choice was 1 prior conviction with
Based on the given sample of student test scores of 50, 60, 74, 83, 83, 90, 90, 92, and 95 after rearranging them from least to greatest. As the mean is based on the average of sum, the average of this sample is 79.67 or 80. The mode refers to numbers that appear the most in a sequence and in this case 83 and 90 both appear twice. Range calculates the difference between the largest and smallest number, which are 95 and 50 which have a difference of 45. The variance is the difference between the sum of squares divided by the sample size, which is the number in the sample minus one (Hansen & Myers, 2012), meaning it takes each number of the set and subtracts
Indicating the individual number 65 gives a 5 point range to the mean. It seems the median is the most accurate way to discribe the data set, as it uneffected by the outlier value.
-The shape of both data sets fall within the rule of thumb estimate and that actual standard deviation. There is a much high range for both and that is because there are several data samples that fall outside of the standard deviation.
These represent the range of the sale price. Lastly, I used the formula to get the standard deviation 48,945.28, which measures the variability.
Anything that has a measurable characteristic that varies is variable which may change from group to group, a person to person, or even within one person over time. To understand more precisely of what is variable we will deal with the two types of concepts: those that refer to fixed phenomenon and those that vary in quantity, intensity, or amount. The second concept and measures of the concept are variables. A variable is defined as anything that varies or changes in value. It represents a quality that can exhibit differences in values, usually magnitude or strength, it is said anything that may assume different numerical or categorical values. Variables is everywhere to support this we can take examples like, gender is a variable. Two values, male and female, marital status is also a variable, never married, married, divorced or widowed. A person’s attitude toward women empowerment is variable; it range from highly favourable to highly unfavourable. A variable may also be situation specific, example gender is variable, but if in a particular situation like in a class if