EPT
发表于 2025-3-27 00:47:56
Confidence Intervals,g estimators are usually called point estimators, but we can go one step further and specify a range for plausible population parameters. This procedure is called interval estimation, and the calculated intervals are labeled .. This chapter introduces the general form of a confidence interval and th
albuminuria
发表于 2025-3-27 04:32:58
http://reply.papertrans.cn/95/9415/941492/941492_32.png
无能力
发表于 2025-3-27 08:25:09
http://reply.papertrans.cn/95/9415/941492/941492_33.png
alcohol-abuse
发表于 2025-3-27 09:50:32
http://reply.papertrans.cn/95/9415/941492/941492_34.png
IRATE
发表于 2025-3-27 14:10:45
Repeated-Measures Analysis of Variance (ANOVA),seen as generalizing the .-test for two dependent samples to more than two samples (or conditions). Accordingly, the present focus is on the performance changes . each participant again. In order to understand the principle of repeated-measures ANOVA, the chapter begins by considering a simplified m
CYN
发表于 2025-3-27 17:53:41
Correlation and Regression,ype of correlation hypotheses. We begin with clarifying what a statistical relationship (or statistical dependence) actually is. Next, we derive the correlation coefficient as a measure to capture linear relationships. This is followed by a take on simple linear regression, which is another way of a
MERIT
发表于 2025-3-28 01:11:20
http://reply.papertrans.cn/95/9415/941492/941492_37.png
激励
发表于 2025-3-28 04:38:58
http://reply.papertrans.cn/95/9415/941492/941492_38.png
南极
发表于 2025-3-28 08:48:02
Textbook 20231st edition statistics. Our major focus is on the logic of inferential statistics and hypothesis testing: We cover the logic behind statistical tests, we then walk through the most common procedures (t-test, analysis of variance with and without repeated measures, correlation/regression) and discuss pitfalls o
biosphere
发表于 2025-3-28 13:17:13
Introduction to Inferential Statistics 1: Random Variables,ariables, which is most relevant for the methods described in later chapters. For continuous random variables, we specifically focus on the normal distribution, which plays a central role in inferential statistics.