EBook Problems - Revision history

Tdlee: Text replacement - "{{translate|pageName=http://wiki.stat.ucla.edu/socr/" to ""{{translate|pageName=http://wiki.socr.umich.edu/"

2020-03-03T17:29:11Z

Text replacement - "{{translate|pageName=http://wiki.stat.ucla.edu/socr/" to ""{{translate|pageName=http://wiki.socr.umich.edu/"

2010-12-14T06:37:30Z

‎V. Normal Probability Distribution: added Multivariate Normal Problems

2008-12-28T23:42:15Z

‎VII. Point and Interval Estimates

2008-12-09T06:15:59Z

‎Statistics with Tools (Calculators and Computers)=

2008-11-27T08:37:17Z

‎Variation and Prediction Intervals

2008-11-27T08:25:41Z

‎Regression

2008-11-27T08:06:15Z

‎Correlation

2008-11-27T07:52:44Z

‎Testing a Claim about a Proportion

2008-11-27T07:49:43Z

‎Testing a Claim about a Mean: Small Samples

2008-11-27T07:45:14Z

‎Testing a Claim about a Mean: Large Samples

← Older revision		Revision as of 17:29, 3 March 2020
Line 284:		Line 284:
	* [http://moodle.stat.ucla.edu UCLA Statistics Moodle]		* [http://moodle.stat.ucla.edu UCLA Statistics Moodle]

−	{{translate\|pageName=http://wiki.~~stat~~.~~ucla~~.edu~~/socr~~/index.php?title=EBook_Problems}}	+	"{{translate\|pageName=http://wiki.socr.umich.edu/index.php?title=EBook_Problems}}

@@ Line 115: / Line 115: @@
 In addition to being able to compute probability (p) values, we often need to estimate the critical values of the Normal Distribution for a given p-value.
 ===[[EBook_Problems_Normal_Critical | Problems]]===
 =VI. Relations Between Distributions=

@@ Line 163: / Line 163: @@
 ===[[EBook_Problems_StudentsT | Problems]]===
-===[[AP_Statistics_Curriculum_2007_Estim_Proportion |Estimating a Population Proportion]]===
+==[[AP_Statistics_Curriculum_2007_Estim_Proportion |Estimating a Population Proportion]]==
 '''Normal Distribution''' is appropriate model for proportions, when the sample size is large enough. In this section, we demonstrate how to obtain point and interval estimates for population proportion.

@@ Line 17: / Line 17: @@
 ===[[EBook_Problems_EDA_IntroDesign | Problems]]===
-==[[AP_Statistics_Curriculum_2007_IntroTools |Statistics with Tools (Calculators and Computers)]]===
+==[[AP_Statistics_Curriculum_2007_IntroTools |Statistics with Tools (Calculators and Computers)]]==
 All methods for data analysis, understanding or visualizing are based on models that often have compact analytical representations (e.g., formulas, symbolic equations, etc.) Models are used to study processes theoretically. Empirical validations of the utility of models are achieved by inputting data and executing tests of the models. This validation step may be done manually, by computing the model prediction or model inference from recorded measurements. This process may be possible by hand, but only for small numbers of observations (<10). In practice, we write (or use existent) algorithms and computer programs that automate these calculations for better efficiency, accuracy and consistency in applying models to larger datasets.
 ===[[EBook_Problems_EDA_IntroTools | Problems]]===

@@ Line 227: / Line 227: @@
 ==[[AP_Statistics_Curriculum_2007_GLM_Predict |Variation and Prediction Intervals]]==
 In this section, we discuss point and interval estimates about the slope of linear models.
 ===[[EBook_Problems_GLM_Predict | Problems]]===

@@ Line 223: / Line 223: @@
 ==[[AP_Statistics_Curriculum_2007_GLM_Regress |Regression]]==
 We are now ready to discuss the modeling of linear relations between two variables using '''Regression Analysis'''. This section demonstrates this methodology for the SOCR California Earthquake dataset.
 ===[[EBook_Problems_GLM_Regress | Problems]]===

@@ Line 219: / Line 219: @@
 ==[[AP_Statistics_Curriculum_2007_GLM_Corr |Correlation]]==
 The '''Correlation''' between X and Y represents the first bivariate model of association which may be used to make predictions.
 ===[[EBook_Problems_GLM_Corr | Problems]]===

@@ Line 189: / Line 189: @@
 ==[[AP_Statistics_Curriculum_2007_Hypothesis_Proportion |Testing a Claim about a Proportion]]==
 When the sample size is large, the sampling distribution of the sample proportion <math>\hat{p}</math> is approximately Normal, by [[AP_Statistics_Curriculum_2007_Limits_CLT | CLT]]. This helps us formulate hypothesis testing protocols and compute the appropriate statistics and p-values to assess significance.
 ===[[EBook_Problems_Hypothesis_Proportion | Problems]]===

@@ Line 185: / Line 185: @@
 ==[[AP_Statistics_Curriculum_2007_Hypothesis_S_Mean |Testing a Claim about a Mean: Small Samples]]==
 We continue with the discussion on inference for the population mean for small samples.
 ===[[EBook_Problems_Hypothesis_S_Mean | Problems]]===

@@ Line 181: / Line 181: @@
 ==[[AP_Statistics_Curriculum_2007_Hypothesis_L_Mean |Testing a Claim about a Mean: Large Samples]]==
 As we already saw how to construct point and interval estimates for the population mean in the large sample case, we now show how to do hypothesis testing in the same situation.
 ===[[EBook_Problems_Hypothesis_L_Mean | Problems]]===