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Question
The Morris water maze is used to examine spatial learning in animals. Mice, who are good swimmers, are placed in a large pool of water and must learn to find a clear platform located just under the water surface. The platform is their only escape from the pool. If they do not find the platform, they have to continue swimming until we take them out.When mice perform in a Morris Water maze they sometimes become confused on a particular trial and take a long time to get to the platform. On other trials they are just lucky and go straight to it. How can we eliminate or reduce the influence of these unusual times?
a) compare medians instead of means
b) use trimmed means
c) toss out scores that we don"t like
d) both a and b
Answer
This answer is hidden. It contains 1 characters.
Related questions
Q:
58 What happens to the standard deviation when a constant is added to each score? Use the following set of data, and a constant of 2 to illustrate your answer.
1 2 3 4
Q:
57 Create two sets of scores with equal ranges, but different variances.
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55 Based on the same data, calculate:
a) The median location
b) The median
c) The hinge location
d) The upper hinge
e) The lower hinge
f) H spread
g) Lower fence
h) Upper fence
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a) interquartile range
b) boxplot
c) range
d) trimmed statistics
Q:
18+ People in the stock market refer to a measure called the "standard deviation," although it is calculated somewhat differently from the one discussed here. It is a good guess that this measure refers toa) the riskiness of the stock.b) the value of the stock.c) how much the stock price is likely to fluctuate.d) how much money you are likely to earn from buying that stock.
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15+ Data points at the extremes of the distribution have
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d) a statistic whose long range average is equal to the parameter it estimates
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Q:
44 Algebraically, the mean = (ï“X)2/N.
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35 Which of the following is probably most useful in studies in which extreme scores sometimes occur but have no real practical significance?
a) mean
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28 For the following data set [1, 9, 9, 9, 11, 28], which of the following is false?
a) The mode is 9.
b) The median is 9.
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21 Suppose a sample of children reported how many voices they heard in their heads on a particular day, and that hearing voices was a relatively uncommon experience. In this case the mode
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18 is the symbol commonly used for the
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Q:
13 The chief advantage of the median is that
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b) it is best used with nominal scales.
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d) it is the most commonly occurring score.
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11+ Given the numbers 6 7 9 11 15 71 86, how many numbers fall below the median?
a) 3
b) 11
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d) 6, 7, 9, and 11
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7+ Which of the following is useful with data collected with nominal scales?
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10 When we plot a histogram, the values on the X axis are
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Q:
36 Multiple regression analysis yielded the following regression equation:
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20 If we find all of the residuals when predicting our obtained values of Y from the regression equation, the sum of squared residuals would be expected to be _______ the sum of the squared residuals for a new set of data.
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a) 11.7
b) 10
c) 16
d) -3
Q:
2+ Assume that we generated a prediction just by adding together the number of stressful events you report experiencing over the last month, the number of close friends you have, and your score on a measure assessing how much control you feel you have over events in your life (i.e., prediction = stress + friends + control). The regression coefficient for stressful events would be
a) 1.0
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c) 0.0
d) There is no way to know.
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20+ When we think in terms of standardized data, the slope represents
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b) the number of standard deviations will differ for a one standard deviation difference in X.
c) the height of the regression line.
d) 0.
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17 In the equation = 12.6 X + 5
a) a difference of one unit in X will lead to a 5 point difference in the prediction.
b) will decrease as X increases.
c) the correlation is certain to be significant.
d) a difference of one unit in X will lead to a 12.6 point difference in the prediction.
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13 The "best fitting line" is that regression line that
a) minimizes the errors of prediction.
b) minimizes each squared error of prediction.
c) minimizes the sum of squared errors of prediction.
d) hits the most points as it goes through the scatterplot.