Table 1.

Paper statistics

FigureComparisonData structure (Shapiro–Wilk normality test unless otherwise stated)Type of testStatisticConfidence, 95% CI
a1CNTG vs hAPPNormal distribution (D’Agostino & Pearson normality test chosen due to multiple duplicate values)Unpaired two-tailed t testt = 0.04476 df = 29p = 0.9646; CI: −0.8191 to 0.7841
b1DNTG vs hAPPNormal distribution (D’Agostino & Pearson Normality Test chosen due to multiple duplicate values)Unpaired two-tailed t testt = 0.3928 df = 27p = 0.6975; CI: −0.9669 to 1.425
c1ENTG vs hAPPNormal distributionUnpaired two-tailed t testt = 3.093 df = 28p = 0.0045; CI: −15.53 to -3.156
d1FNTG vs hAPPNormal distributionUnpaired two-tailed t testt = 0.1181 df = 31p = 0.9067; CI: −2.015 to 1.794
e12BOvarian status by hour interactionNormal distributionMixed-model ANOVAF(22,88) = 2.05p = 0.0097
e22BOvarian status effectNormal distributionMixed Model ANOVAF(2,110) = 20.89p < 0.0001
e32BMetestrus/Diestrus vs ProestrusNormal distributionBonferroni–Holm Corrected p < 0.0001; CI: −18.615 to -9.899
e42BProestrus vs GnxNormal distributionBonferroni–Holm Corrected p = 0.0156; CI: 4.538 to 32.026
e52BMetestrus/Diestrus vs GnxNormal distributionBonferroni–Holm Corrected p = 0.5581; CI: −9.719 to 17.769
f12CProestrus after vs beforeNormal distributionPaired one-tailed t testt = 3.851 df = 2p = 0.0307; CI: 8.136 to ∞
f22CBefore E2 surgeNormal distributionOne-way ANOVAF(2,8) = 0.2880p = 0.7572
f32CAfter E2 surgeNormal distributionOne-way ANOVAF(2,8) = 8.534p = 0.0104
f42CAfter surge: metestrus/diestrus vs proestrusNormal distributionBonferroni–Holm Correctedt = 3.129 df = 8p = 0.0421; CI: −66.77 to -1.234
f52CAfter surge: proestrus vs GnxNormal distributionBonferroni–Holm Correctedt = 3.986 df = 8p = 0.0121; CI: 9.427 to 68.04
f62CAfter surge: metestrus/diestrus vs GnxNormal distributionBonferroni–Holm Correctedt = 0.4871 df = 8p > 0.9999; CI: −24.57 to 34.04
g13AOvarian status by genotype interactionNormal distributionTwo-way ANOVAF(2,34) = 1.365p = 0.2690
g23AOvarian status effectNormal distributionTwo-way ANOVAF(2,34) = 1.776p = 0.1846
g33AGenotype effectNormal distributionTwo-way ANOVAF(1,34) = 0.01396p = 0.9066
g43A,BTraining vs testing latencyNormal distributionLinear regressionF(1,35) =1.559p = 0.2202; p = 0.1049-0.7498 for each experimental group
h13BOvarian status by genotype interactionNormal distributionTwo-way ANOVAF(2,31) = 4.88p = 0.0144
h23BOvarian status effectNormal distributionTwo-way ANOVAF(2,31) = 0.497p = 0.631
h33BGenotype effectNormal distributionTwo-way ANOVAF(1,31) = 2.323p = 0.1376
h43BhAPP-High E/P vs hAPP-Low E/PNormal distributionBonferroni–Holm Correctedt = 3.126 df = 6p = 0.041; CI: −186.5 to −22.73
h53BhAPP-High E/P vs NTG-High E/PNormal distributionBonferroni–Holm Correctedt = 3.969 df = 6p = 0.022; CI: −211.1 to −50.07
h63BhAPP-Low E/P vs NTG-Low E/PNormal distributionBonferroni–Holm Correctedt = 1.149 df = 10p = 0.275; CI: −34.47 to 107.8
h73BGnx hAPP vs Gnx NTG, Reference for Cycling MiceNormal distributionUnpaired two-tailed t testt = 0.04699 df = 15p = 0.9631; CI: −71.92 to 68.82
i13ChAPP: % Time in High E/P & LatencyNormal distributionLinear regressionR 2 = 0.7144p = 0.0041; CI (slope): −5.078 to −1.411
i23CNTG: % Time in High E/P & LatencyNormal distributionLinear regressionR 2 = 1.334e-005p = 0.9910; CI (slope): −3.702 to 3.664
j14ANTG-High E/P: Novel vs FamiliarNormal distributionPaired one-tailed t testt = 3.367 df = 9p = 0.0042; CI: 0.5634 to ∞
j24ANTG-Low E/P: Novel vs FamiliarNormal distributionPaired one-tailed t testt = 7.912 df = 3p = 0.0021; CI: 1.212 to ∞
j34AhAPP-High E/P: Novel vs FamiliarNormal distributionPaired one-tailed t testt = 0.9654 df = 11p = 0.1775; CI: −0.3776 to ∞
j44AhAPP-Low E/P: Novel vs FamiliarFamiliar: normal distribution; Novel : not-normal (p = 0.0167)Paired one-tailed t testt = 2.066 df = 6p = 0.0422; CI: 0.05542 to ∞
j54BhAPP-High E/P vs theoretical mean (31.33)Normal distributionTwo-tailed one sample t testt = 2.525 df = 11p = 0.0282; CI: −6.665 to -0.4568
j64-1Ovarian status effectNormal distributionTwo-way ANOVAF(1,35) = 0.5209p = 0.4752
j74-1Genotype effectNormal distributionTwo-way ANOVAF(1,35) = 1.448p = 0.2370
j84-1Ovarian status by genotype interactionNormal distributionTwo-way ANOVAF(1,35) = 0.17p = 0.6826
k15Ovarian status by genotype interactionNormal distribution except hAPP Met/Di (p = 0.0382)Two-way ANOVAF(2,41) = 0.9277p = 0.4036
k25Ovarian status effectNormal distribution except hAPP Met/Di (p = 0.0382)Two-way ANOVAF(2,41) = 3.501p = 0.0395
k35Genotype effectNormal distribution except hAPP Met/Di (p = 0.0382)Two-way ANOVAF(1,41) = 36.95p < 0.0001
k45hAPP-High E/P vs hAPP-Low E/PNormal distribution except hAPP Met/Di (p = 0.0382)Unpaired two-tailed t testt = 2.559 df = 8p = 0.0337; CI: −1211 to −62.90
l6BhAPP Met/Di vs ProestrusNormal distributionUnpaired two-tailed t testt = 4.319 df = 10p = 0.0015; CI: −0.8811 to −0.2814
m6DhAPP Met/Di vs ProestrusNormal distributionUnpaired two-tailed t testt = 1.107 df = 11p = 0.2921; CI: −0.1201 to 0.3628
n6FhAPP Met/Di vs ProestrusNormal distributionUnpaired two-tailed t testt = 1.798 df = 10p = 0.1024; CI: −0.4675 to 0.04995
o6GhAPP Met/Di vs ProestrusNormal distributionUnpaired two-tailed t testt = 0.4533 df = 11p = 0.6591; CI: −0.3629 to 0.2389
p6HhAPP Met/Di vs ProestrusNormal distributionUnpaired two-tailed t testt = 0.149 df = 11p = 0.8842; CI: −0.5582 to 0.4874
q7AGenotype by Treatment InteractionNormal distribution (D’Agostino & Pearson normality test chosen due to multiple duplicate values)Linear mixed-model p = 0.017; CI: −829.9 to -80.8
r17BGenotype by treatment interactionNormal distribution for NTG and hAPP Veh; N too small to determine if Gaussian for NTG and hAPP E2 (D’Agostino & Pearson normality test chosen due to multiple duplicate values)Two-way ANOVAF(1,26) = 5.157p = 0.0317
r27BGenotype effectNormal distribution for NTG and hAPP Veh; N too small to determine if Gaussian for NTG and hAPP E2 (D'Agostino & Pearson normality test chosen due to multiple duplicate values)Two-way ANOVAF(1,26) = 7.982p = 0.009
r37BTreatment effectNormal distribution for NTG and hAPP Veh; N too small to determine if Gaussian for NTG and hAPP E2 (D’Agostino & Pearson normality test chosen due to multiple duplicate values)Two-way ANOVAF(1,26) = 0.7303p = 0.4006
r47BGnx-E2: NTG vs hAPPNormal distribution for NTG and hAPP Veh; N too small to determine if Gaussian for NTG and hAPP E2 (D’Agostino & Pearson normality test chosen due to multiple duplicate values)Bonferroni–Holm Correctedt = 3.701 df = 12p = 0.006; CI: 301.7 to 1165
r57BGnx-Veh: NTG vs hAPPNormal distribution for NTG and hAPP Veh; N too small to determine if Gaussian for NTG and hAPP E2 (D’Agostino & Pearson normality test chosen due to multiple duplicate values)Bonferroni–Holm Correctedt = 0.3877 df = 14p = 0.7041; CI: −521.3 to 361.7
s17CGnx-E2: NTG vs hAPPCategorical dataχ2 TestPearson χ2(1,n = 14) = 7.7778p = 0.005
s27CGnx-Veh: NTG vs hAPPCategorical dataχ2 TestPearson χ2(1,n = 16) = 0.2909p = 0.590
t7DGnx-hAPP: Veh vs E2Normal distributionUnpaired two-tailed t testt = 2.239 df = 19p = 0.0373; CI: −0.6 to −0.02019