## Statistics for the TerrifiedAn introduction to statistics for the social sciences. This text aims to give students an understanding of the concepts and computations of basic statistics and to train them to overcome math anxiety and avoidance responses that interfere with learning. |

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THE MEDIAN (Md) When scores are arranged in order, from highest to lowest (or

lowest to highest), the median is the middle score. Suppose you administered an

IQ test to five persons who scored as follows: 113, 133, 95, 112, 94. To find the

median, you would first arrange all scores in numerical order and then find the

middle score. Example

example, 112 is the median score because, when scores are arranged in order ...

THE MEDIAN (Md) When scores are arranged in order, from highest to lowest (or

lowest to highest), the median is the middle score. Suppose you administered an

IQ test to five persons who scored as follows: 113, 133, 95, 112, 94. To find the

median, you would first arrange all scores in numerical order and then find the

middle score. Example

**IQ Scores**133 113 112 median = Md = 112 95 94 In ourexample, 112 is the median score because, when scores are arranged in order ...

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The three measures of central tendency always coincide in any group of scores

that is normally distributed. Recall that the median is the middle score, the score

that divides a group of scores exactly in half. For any distribution, you know that

50% of the scores are below the median and 50% above. In a normal distribution

the median equals the mean, so you know that 50% of the scores also are higher

and lower than the mean. Thus, if you know that the mean of a group of

is ...

The three measures of central tendency always coincide in any group of scores

that is normally distributed. Recall that the median is the middle score, the score

that divides a group of scores exactly in half. For any distribution, you know that

50% of the scores are below the median and 50% above. In a normal distribution

the median equals the mean, so you know that 50% of the scores also are higher

and lower than the mean. Thus, if you know that the mean of a group of

**IQ scores**is ...

Page 65

Using the data from the problem set at the end of the last chapter, find the

regression equation that would be used to predict a. anxiety scores, if you know

the

scores, if you know the anxiety scores. 2. Given these regression equations, what

would you predict as an anxiety score for a person who scored 125 on the IQ test

? What about that person's statistics score? What statistics score would you

predict for ...

Using the data from the problem set at the end of the last chapter, find the

regression equation that would be used to predict a. anxiety scores, if you know

the

**IQ scores**. b. statistics test scores, if you know the**IQ scores**. c. statistics testscores, if you know the anxiety scores. 2. Given these regression equations, what

would you predict as an anxiety score for a person who scored 125 on the IQ test

? What about that person's statistics score? What statistics score would you

predict for ...

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### Contents

Introduction to Inferential Statistics | 67 |

Differences between the Means of Two Groups | 75 |

Oneway Analysis of Variance | 88 |

Copyright | |

4 other sections not shown

### Other editions - View all

Statistics for the Terrified John H. Kranzler,Gerald Kranzler,Janet Moursund No preview available - 2007 |

### Common terms and phrases

05 level Activating event ANOVA answer Appendix chance Chapter classroom column compute control group correlation coefficient counselor touch critical value decimal denominator divide empathy equal equation example feel fobt formula frequency polygon graph independent samples indicate inferential statistics intelligence test scores IQ scores learned level of significance look median multiply negative numbers nonparametric norm group normal curve normally distributed Notice null hypothesis number of scores number of subjects one-tailed test pair parametric parentheses percentile rank pi pi pi population posttest predicted predictor PROBLEMS random numbers raw score reject H0 reject the null relationship researcher Rule Ruritania sample means self-talk sg sg skewed square root ss ss standard deviation standard scores statistically significant statistics test Step subtracting sum of squares Suppose tc"t test for independent thing tobt toht total number two-tailed test Type I error variables variance