Index of papers in March 2015 that mention

**t-test**

Relationship of Csparse+latent to orientation tuning and physical distances | 7 A and D. p < 10'9 in each of the five sites, two-sample t-test of the difference of the linear regression coefficients in normalized data). |

Relationship of Csparse+latent to orientation tuning and physical distances | Positive connectivity decreased with Aori (p < 0.005 in each of the five sites, t-test on the logistic regression coefficient) whereas negative connectivity did not decrease (Fig. |

Relationship of Csparse+latent to orientation tuning and physical distances | 7 G): The slope in the logistic model of connectivity with respect to Aori was significantly higher for positive than for negative interactions (p < 0.04 in each of the five sites, two-sample t-test of the difference of the logistic regression coefficient). |

t-test is mentioned in 6 sentences in this paper.

Topics mentioned in this paper:

Learning rates | This was done by moving a sliding window (width 50 trials) across the normalised training extent and performing a t-test for each point in time. |

Learning rates | The trial at which the t-test indicated that the normalised learning extent after that trial was significantly above zero (at an a-level of 0.000625 for Bonferroni correction) was taken as the time point at which participants realised the role of the shape and started to learn the mappings. |

inter Iation test sha es '—' extrapolation W p extrapolation test shape shape parameter p test shape | This difference in the amount of learning between the two conditions was significant ( t-test , p = 0.03) even with our relatively small sample size. |

inter Iation test sha es '—' extrapolation W p extrapolation test shape shape parameter p test shape | It turns out that even for this comparison, when the number of examples per pair are equalised across conditions, the learning extent in the 2-Pair Condition is significantly larger than the 5-Pair Condition ( t-test , p = 0.02). |

t-test is mentioned in 4 sentences in this paper.

Topics mentioned in this paper:

- ANOVA (5)
- t-test (4)
- associative learning (3)