Normal Distribution and Points

1. A formal statement that there is an absence of relationship between variables when tested by a researcher is called: (Points : 1) | Null hypothesis Type I error Type II error Negative interval |

2. Bivariate statistics refers to the statistical analysis of the relationship between two variables. (Points : 1) | True False |

3. Positive relationships between two variables indicate that, as the score of one increases, the score of the other increases. (Points : 1) | True False |

4. A result that is probably not attributable to chance is: (Points : 1) | Type I error Type II error Statistical significance In the semi-quartile range |

5. A score that is likely to fall into the middle 68% of scores of a normal distribution will fall inside these values: (Points : 1) | . +/- 3 standard deviations +/- 2 standard deviations +/- 1 standard deviation semi-quartile range |

6. It is important to assess the magnitude or strength of a relationship because this assists you with deciding whether or not a variable A causes variable B. (Points : 1) | True False |

7. In a negative relationship, as the score of one variable decreases, the score on the second variable decreases. (Points : 1) | True False |

8. A set of subjects, usually randomly sampled, selected to participate in a research study is called: (Points : 1) | Population Sample Mode Group Partial Selection |

9. A perfect negative relationship between two variables is expressed as r=0. (Points : 1) | True False |

10. When examining the relationship between a nominal variable and an interval or ratio variable, you would create a table using the nominal variables, calculate the mode and median of the interval or ratio variable, then make a