The document describes the Cochran-Mantel-Haenszel method for adjusting odds ratios when analyzing the relationship between a dichotomous risk factor and outcome while controlling for confounding factors. It provides an example looking at the relationship between catecholamine levels and coronary heart disease, adjusting for age and ECG changes. The Mantel-Haenszel method is used to calculate an adjusted odds ratio of 1.89, indicating those with high catecholamine levels have nearly twice the odds of coronary heart disease after accounting for confounders. The Breslow-Day test is then described as a method to assess the homogeneity of odds ratios across strata.
This document discusses p-values and their significance in statistical hypothesis testing. It defines a p-value as the probability of obtaining a result equal to or more extreme than what was observed assuming the null hypothesis is true. Lower p-values indicate stronger evidence against the null hypothesis. The document outlines the steps in hypothesis testing which include stating hypotheses, determining acceptable type I and type II error rates, selecting a statistical test to calculate a test statistic, determining the p-value, making inferences, and forming conclusions. It emphasizes that statistical significance does not necessarily imply real-world significance.
1) Meta-analysis is a statistical technique that combines the results of multiple studies on a topic and produces a single estimate of the overall effect. It aims to increase power by pooling data.
2) The first meta-analysis was conducted in 1904, and the term was coined in 1976. Meta-analysis is now often called a "systematic review."
3) Meta-analysis can help clinicians and policymakers integrate research findings and determine if relationships are consistent across studies. It increases precision and statistical power compared to individual studies.
This document discusses tests of significance and summarizes key concepts. It begins by describing qualitative and quantitative data and measures of central tendency. It then discusses sampling variation, the null hypothesis, p-values, and the standard error. The document outlines the steps in hypothesis testing and describes different types of tests including the standard error of difference between two proportions (SEDP) test and the chi-square test. Examples are provided to demonstrate how to calculate test statistics and determine significance. The limitations of the SEDP test are also noted.
This document discusses meta-analysis techniques for systematically reviewing and statistically combining results from multiple clinical trials. It covers the history of meta-analysis, methodology for combining test statistics and assessing heterogeneity, software for conducting meta-analyses, and current issues including how to handle different study designs. Examples are provided to illustrate meta-analysis of randomized controlled trials comparing treatments for stroke, myocardial infarction, and other conditions.
This document discusses meta-analysis, which involves systematically combining results from multiple studies to derive conclusions about a body of research. It describes the key steps in conducting a meta-analysis, including writing a research question and protocol, performing a comprehensive literature search, selecting studies, assessing study quality, extracting data, and analyzing data. Statistical methods for pooling results across studies using fixed and random effects models are also outlined. The document highlights strengths and limitations of meta-analysis for providing more precise estimates of treatment effects and identifying areas needing further research.
ANOVA tests determine if there are differences in group means but do not specify which pairs differ. Post hoc tests identify the pairs of means that are significantly different. Tukey's HSD test and Fisher's LSD test can be used when variances are equal between groups. The Games Howell test is recommended when variances are not equal.
This course is designed to give students an overview of research versus biostatistics, Stata, test of association, comparisons of means, Correlation and regression, Generalized Linear Models (GLM).
The sessions are designed to introduce the denitions and basic
concepts of biostatistics, statistical inference, t-test, ANOVA, Correlation, Linear regression, logistic regression, Poisson regression, Negative binomial regression, and Zero in
ated poisson regression.
The overall emphasis will be placed on understanding the language of statistics and the art of statistical investigation.
This document discusses p-values and their significance in statistical hypothesis testing. It defines a p-value as the probability of obtaining a result equal to or more extreme than what was observed assuming the null hypothesis is true. Lower p-values indicate stronger evidence against the null hypothesis. The document outlines the steps in hypothesis testing which include stating hypotheses, determining acceptable type I and type II error rates, selecting a statistical test to calculate a test statistic, determining the p-value, making inferences, and forming conclusions. It emphasizes that statistical significance does not necessarily imply real-world significance.
1) Meta-analysis is a statistical technique that combines the results of multiple studies on a topic and produces a single estimate of the overall effect. It aims to increase power by pooling data.
2) The first meta-analysis was conducted in 1904, and the term was coined in 1976. Meta-analysis is now often called a "systematic review."
3) Meta-analysis can help clinicians and policymakers integrate research findings and determine if relationships are consistent across studies. It increases precision and statistical power compared to individual studies.
This document discusses tests of significance and summarizes key concepts. It begins by describing qualitative and quantitative data and measures of central tendency. It then discusses sampling variation, the null hypothesis, p-values, and the standard error. The document outlines the steps in hypothesis testing and describes different types of tests including the standard error of difference between two proportions (SEDP) test and the chi-square test. Examples are provided to demonstrate how to calculate test statistics and determine significance. The limitations of the SEDP test are also noted.
This document discusses meta-analysis techniques for systematically reviewing and statistically combining results from multiple clinical trials. It covers the history of meta-analysis, methodology for combining test statistics and assessing heterogeneity, software for conducting meta-analyses, and current issues including how to handle different study designs. Examples are provided to illustrate meta-analysis of randomized controlled trials comparing treatments for stroke, myocardial infarction, and other conditions.
This document discusses meta-analysis, which involves systematically combining results from multiple studies to derive conclusions about a body of research. It describes the key steps in conducting a meta-analysis, including writing a research question and protocol, performing a comprehensive literature search, selecting studies, assessing study quality, extracting data, and analyzing data. Statistical methods for pooling results across studies using fixed and random effects models are also outlined. The document highlights strengths and limitations of meta-analysis for providing more precise estimates of treatment effects and identifying areas needing further research.
ANOVA tests determine if there are differences in group means but do not specify which pairs differ. Post hoc tests identify the pairs of means that are significantly different. Tukey's HSD test and Fisher's LSD test can be used when variances are equal between groups. The Games Howell test is recommended when variances are not equal.
This course is designed to give students an overview of research versus biostatistics, Stata, test of association, comparisons of means, Correlation and regression, Generalized Linear Models (GLM).
The sessions are designed to introduce the denitions and basic
concepts of biostatistics, statistical inference, t-test, ANOVA, Correlation, Linear regression, logistic regression, Poisson regression, Negative binomial regression, and Zero in
ated poisson regression.
The overall emphasis will be placed on understanding the language of statistics and the art of statistical investigation.
Survival analysis is used to analyze time-to-event data from clinical studies where some subjects may be censored. Survival time refers to the time from treatment start to an endpoint. Censoring occurs when the exact event time is unknown. The Kaplan-Meier method estimates the survival function by assigning weights to observations and redistributing weights from censored observations. The log-rank test compares survival curves between groups. Cox proportional hazards models analyze the relationship between survival time and variables while adjusting for other factors.
This document discusses key statistical concepts including p-values, type I and II errors, power, and sample size. It defines p-value as the probability of obtaining results as extreme or more extreme than what was observed. Type I error is rejecting the null hypothesis when it is true, while type II error is failing to reject the null when it is false. Power is the probability of avoiding a type II error. The relationships between these concepts and how factors like sample size and effect size influence them are explained. Sample size calculations must consider the desired power, significance level, population variability, and minimum effect size to detect.
A systematic review is a rigorous analysis of published research on a focused question that collects and summarizes the evidence. It contrasts with an overview, which may include non-research articles and be influenced by other evidence. Meta-analysis uses statistical methods to combine results from multiple studies. To ensure validity, meta-analyses must have a well-defined methodology, including comprehensive searches and duplicate screening and data extraction to reduce bias. Important factors include assessing whether all relevant studies were found and the sources searched, as well as controlling for biases such as from selective data extraction or funding influences.
This meta-analysis examined the relationship between body mass index (BMI) and incident asthma. It identified 2006 relevant studies and included 12 prospective cohort studies. Inclusion criteria required adult subjects, asthma as the primary outcome, BMI measurement, minimum 1-year follow up of 70%, and BMI data categorized by standard ranges. Random effects models were used to generate summary odds ratios. Results showed overweight individuals had a 38% higher odds of developing asthma compared to normal weight, and obese individuals had 92% higher odds. When stratified by sex, the association was stronger for women. The analysis provided evidence that higher BMI is a risk factor for incident asthma.
In clinical trials and other scientific studies, an interim analysis is an analysis of data that is conducted before data collection has been completed. If a treatment is particularly beneficial or harmful compared to the concurrent placebo group while the study is on-going, the investigators are ethically obliged to assess that difference using the data at hand and to make a deliberate consideration of terminating the study earlier than planned.
In interim analysis, whenever a new drug shows adverse effect on human being while testing the effectiveness of several drugs, we immediately stop the trial by taking into account the fact that maximum number of patients receive most effective treatment at the earliest stage. Interim analysis is also used to possibly reduce the expected number of patients and to shorten the follow-up time needed to make a conclusion. One wouldn't have to spend extra money if he/she already have enough evidence about the outcome. In this presentation, the total sample size is divided into four equal parts to perform the analysis and decision is made based on each individual step.
Hazard ratios compare the instantaneous event rates of subjects in a treatment group to those in a control group. A hazard ratio of 1 means the event rates are the same in both groups. A hazard ratio greater than 1 means events are occurring more frequently in the treatment group, while a hazard ratio less than 1 means events are occurring less frequently in the treatment group compared to the control. Though often interpreted as a relative risk, hazard ratios are not technically measuring the same thing. Hazard ratios provide information about time-to-event analysis and the probability of an event occurring at a specific time point.
Randomization aims to equally distribute participant characteristics between treatment groups to prevent bias. There are several types of randomization including simple, block, and stratified block randomization. Blinding, such as double or triple blinding, helps prevent performance, detection, and other biases by keeping parties unaware of treatment assignments. Bias can still occur through factors like selection, performance, detection, laboratory, or sample size biases if randomization and blinding are not properly implemented.
Randomized controlled trials (RCTs) aim to reduce bias when testing new treatments by randomly allocating participants to either a treatment group or a control group. Random allocation means each participant has an equal probability of being assigned to either group. RCTs can be classified based on their design, such as parallel-group trials where each participant receives either the treatment or control. Blinding of participants and researchers is important to reduce biases. Allocation concealment, such as using opaque sealed envelopes, also helps reduce biases in RCT outcomes.
Meta-analysis in Epidemiology is:
Useful tool for epidemiological studies which investigates the relationships between certain risk factors and disease.
Useful tool to improve animal well-being and productivity
Despite of a wealth of suitable studies it is relatively underutilized in animal and veterinary science.
Meta-analysis can provide reliable results about diseases occurrence, pattern and impact in livestock.
It is utmost essential to take benefit of this statistical tool for produce. more reliable estimates of concern effects in animal and veterinary science data.
Application of Survival Data Analysis- Introduction and Discussion (存活数据分析及应用- 简介和讨论), will give an overview of survival data analysis, including parametric and non-parametric approaches and proportional hazard model, providing a real life example of survival data-based field return analysis. Several common issues in survival data analysis will also be discussed.
This document discusses various types of biases and errors that can occur in epidemiological studies, including random error, systematic error, random misclassification, bias, and confounding. It provides definitions and examples of these terms. Specific types of biases covered include selection bias, information bias, and confounding. Methods for controlling biases discussed include randomization, restriction, matching, stratification, standardization, and blinding.
This document provides an overview of randomized controlled trials (RCTs). It begins with an introduction to RCTs, describing them as the gold standard for evaluating health care technologies. It then covers key aspects of designing and conducting RCTs, including developing a protocol, selecting and randomizing study populations, manipulating variables, follow-up, assessment, types of RCTs based on design and use, and ethical considerations. RCTs aim to provide scientific evidence of causal relationships and evaluate interventions through random assignment and control groups.
The document provides information about binomial probability distributions including:
- Binomial experiments have a fixed number (n) of independent trials with two possible outcomes and a constant probability (p) of success.
- The binomial probability distribution gives the probability of getting exactly x successes in n trials. It is calculated using the binomial coefficient and p and q=1-p.
- The mean, variance and standard deviation of a binomial distribution are np, npq, and √npq respectively.
- Examples demonstrate calculating probabilities of outcomes for binomial experiments and determining if results are significantly low or high using the range rule of μ ± 2σ.
1) A systematic review follows a strict methodology to identify and analyze relevant research on a focused question.
2) The process involves developing a protocol, searching multiple databases, screening studies, assessing bias, and synthesizing data.
3) Reporting guidelines like PRISMA ensure transparency and consistency in reporting systematic reviews.
Randomized controlled trials (RCTs) are experimental studies that assess the effect of an intervention by comparing outcomes between those who receive the intervention and a control group. RCTs minimize bias by randomly assigning participants to groups and concealing group assignments. Key factors in RCTs include sufficient sample size, stratified randomization to balance groups, blinding participants and assessors, and accounting for attrition. RCTs allow for causal inferences but have disadvantages like difficulty with some ethical questions and dropout.
- Cohort studies examine the association between an exposure and an outcome by following groups over time and comparing their experience.
- This document discusses what a cohort study is, how it differs from other study designs in determining temporal relationships, and provides examples of cohort designs and their analysis.
- Key aspects reviewed include prospectively following groups based on exposure status and comparing disease incidence rates and relative risks between exposed and unexposed groups over time.
This document provides an introduction to biostatistics. It defines key biostatistics terms like data, variables, scales of measurement, and methods of data presentation. Descriptive and inferential statistics are introduced. Common measures of central tendency (mean, median, mode) and dispersion (range, standard deviation, variance) are defined for different data types. Common methods for presenting data visually, like histograms, bar graphs and box plots, are also described. The normal distribution is introduced as an important assumption for many statistical tests. Examples are provided to illustrate concepts like using z-scores to determine what proportion of values fall above or below a given cutoff from the mean.
This ppt is all about Biostatistics for Medical, Nursing and Pharmacy Students...
The Essentials of Biostatistics for Physicians, Nurses, and Clinicians
Biostatistics – Lecture Notes/Book (PDF) Nursing
Biostatistics are the development and application of statistical methods to a wide range of topics in biology. It encompasses the design of biological experiments, the collection and analysis of data from those experiments and the interpretation of the results.
Cochran-Mantel-Haenszel Test with Breslow-Day & Tarone CorrectionAzmi Mohd Tamil
This document discusses the Cochran-Mantel-Haenszel (CMH) method for adjusting odds ratios when analyzing the relationship between a dichotomous risk factor and outcome while controlling for potential confounding factors. It provides an example looking at the relationship between catecholamine levels (risk factor) and coronary heart disease (outcome) while adjusting for age and ECG changes (confounders). The CMH method is used to calculate stratum-specific odds ratios, an overall adjusted odds ratio of 1.89, and test for homogeneity across strata, finding no significant interaction between the risk factor and confounders.
The document discusses using a vector autoregression (VAR) model to forecast two time series - leads and binds - that interact with each other. A 5-period VAR model is found to best capture the weekly periodicity between the series. The model is shown to accurately forecast leads 1-11 days in advance, within 2% error, and binds within 5% error over a two week period, indicating the interaction between the series can be used to predict each going forward. Some conclusions drawn are that the VAR model performs well but could be improved by trying other techniques or adding external variables.
Survival analysis is used to analyze time-to-event data from clinical studies where some subjects may be censored. Survival time refers to the time from treatment start to an endpoint. Censoring occurs when the exact event time is unknown. The Kaplan-Meier method estimates the survival function by assigning weights to observations and redistributing weights from censored observations. The log-rank test compares survival curves between groups. Cox proportional hazards models analyze the relationship between survival time and variables while adjusting for other factors.
This document discusses key statistical concepts including p-values, type I and II errors, power, and sample size. It defines p-value as the probability of obtaining results as extreme or more extreme than what was observed. Type I error is rejecting the null hypothesis when it is true, while type II error is failing to reject the null when it is false. Power is the probability of avoiding a type II error. The relationships between these concepts and how factors like sample size and effect size influence them are explained. Sample size calculations must consider the desired power, significance level, population variability, and minimum effect size to detect.
A systematic review is a rigorous analysis of published research on a focused question that collects and summarizes the evidence. It contrasts with an overview, which may include non-research articles and be influenced by other evidence. Meta-analysis uses statistical methods to combine results from multiple studies. To ensure validity, meta-analyses must have a well-defined methodology, including comprehensive searches and duplicate screening and data extraction to reduce bias. Important factors include assessing whether all relevant studies were found and the sources searched, as well as controlling for biases such as from selective data extraction or funding influences.
This meta-analysis examined the relationship between body mass index (BMI) and incident asthma. It identified 2006 relevant studies and included 12 prospective cohort studies. Inclusion criteria required adult subjects, asthma as the primary outcome, BMI measurement, minimum 1-year follow up of 70%, and BMI data categorized by standard ranges. Random effects models were used to generate summary odds ratios. Results showed overweight individuals had a 38% higher odds of developing asthma compared to normal weight, and obese individuals had 92% higher odds. When stratified by sex, the association was stronger for women. The analysis provided evidence that higher BMI is a risk factor for incident asthma.
In clinical trials and other scientific studies, an interim analysis is an analysis of data that is conducted before data collection has been completed. If a treatment is particularly beneficial or harmful compared to the concurrent placebo group while the study is on-going, the investigators are ethically obliged to assess that difference using the data at hand and to make a deliberate consideration of terminating the study earlier than planned.
In interim analysis, whenever a new drug shows adverse effect on human being while testing the effectiveness of several drugs, we immediately stop the trial by taking into account the fact that maximum number of patients receive most effective treatment at the earliest stage. Interim analysis is also used to possibly reduce the expected number of patients and to shorten the follow-up time needed to make a conclusion. One wouldn't have to spend extra money if he/she already have enough evidence about the outcome. In this presentation, the total sample size is divided into four equal parts to perform the analysis and decision is made based on each individual step.
Hazard ratios compare the instantaneous event rates of subjects in a treatment group to those in a control group. A hazard ratio of 1 means the event rates are the same in both groups. A hazard ratio greater than 1 means events are occurring more frequently in the treatment group, while a hazard ratio less than 1 means events are occurring less frequently in the treatment group compared to the control. Though often interpreted as a relative risk, hazard ratios are not technically measuring the same thing. Hazard ratios provide information about time-to-event analysis and the probability of an event occurring at a specific time point.
Randomization aims to equally distribute participant characteristics between treatment groups to prevent bias. There are several types of randomization including simple, block, and stratified block randomization. Blinding, such as double or triple blinding, helps prevent performance, detection, and other biases by keeping parties unaware of treatment assignments. Bias can still occur through factors like selection, performance, detection, laboratory, or sample size biases if randomization and blinding are not properly implemented.
Randomized controlled trials (RCTs) aim to reduce bias when testing new treatments by randomly allocating participants to either a treatment group or a control group. Random allocation means each participant has an equal probability of being assigned to either group. RCTs can be classified based on their design, such as parallel-group trials where each participant receives either the treatment or control. Blinding of participants and researchers is important to reduce biases. Allocation concealment, such as using opaque sealed envelopes, also helps reduce biases in RCT outcomes.
Meta-analysis in Epidemiology is:
Useful tool for epidemiological studies which investigates the relationships between certain risk factors and disease.
Useful tool to improve animal well-being and productivity
Despite of a wealth of suitable studies it is relatively underutilized in animal and veterinary science.
Meta-analysis can provide reliable results about diseases occurrence, pattern and impact in livestock.
It is utmost essential to take benefit of this statistical tool for produce. more reliable estimates of concern effects in animal and veterinary science data.
Application of Survival Data Analysis- Introduction and Discussion (存活数据分析及应用- 简介和讨论), will give an overview of survival data analysis, including parametric and non-parametric approaches and proportional hazard model, providing a real life example of survival data-based field return analysis. Several common issues in survival data analysis will also be discussed.
This document discusses various types of biases and errors that can occur in epidemiological studies, including random error, systematic error, random misclassification, bias, and confounding. It provides definitions and examples of these terms. Specific types of biases covered include selection bias, information bias, and confounding. Methods for controlling biases discussed include randomization, restriction, matching, stratification, standardization, and blinding.
This document provides an overview of randomized controlled trials (RCTs). It begins with an introduction to RCTs, describing them as the gold standard for evaluating health care technologies. It then covers key aspects of designing and conducting RCTs, including developing a protocol, selecting and randomizing study populations, manipulating variables, follow-up, assessment, types of RCTs based on design and use, and ethical considerations. RCTs aim to provide scientific evidence of causal relationships and evaluate interventions through random assignment and control groups.
The document provides information about binomial probability distributions including:
- Binomial experiments have a fixed number (n) of independent trials with two possible outcomes and a constant probability (p) of success.
- The binomial probability distribution gives the probability of getting exactly x successes in n trials. It is calculated using the binomial coefficient and p and q=1-p.
- The mean, variance and standard deviation of a binomial distribution are np, npq, and √npq respectively.
- Examples demonstrate calculating probabilities of outcomes for binomial experiments and determining if results are significantly low or high using the range rule of μ ± 2σ.
1) A systematic review follows a strict methodology to identify and analyze relevant research on a focused question.
2) The process involves developing a protocol, searching multiple databases, screening studies, assessing bias, and synthesizing data.
3) Reporting guidelines like PRISMA ensure transparency and consistency in reporting systematic reviews.
Randomized controlled trials (RCTs) are experimental studies that assess the effect of an intervention by comparing outcomes between those who receive the intervention and a control group. RCTs minimize bias by randomly assigning participants to groups and concealing group assignments. Key factors in RCTs include sufficient sample size, stratified randomization to balance groups, blinding participants and assessors, and accounting for attrition. RCTs allow for causal inferences but have disadvantages like difficulty with some ethical questions and dropout.
- Cohort studies examine the association between an exposure and an outcome by following groups over time and comparing their experience.
- This document discusses what a cohort study is, how it differs from other study designs in determining temporal relationships, and provides examples of cohort designs and their analysis.
- Key aspects reviewed include prospectively following groups based on exposure status and comparing disease incidence rates and relative risks between exposed and unexposed groups over time.
This document provides an introduction to biostatistics. It defines key biostatistics terms like data, variables, scales of measurement, and methods of data presentation. Descriptive and inferential statistics are introduced. Common measures of central tendency (mean, median, mode) and dispersion (range, standard deviation, variance) are defined for different data types. Common methods for presenting data visually, like histograms, bar graphs and box plots, are also described. The normal distribution is introduced as an important assumption for many statistical tests. Examples are provided to illustrate concepts like using z-scores to determine what proportion of values fall above or below a given cutoff from the mean.
This ppt is all about Biostatistics for Medical, Nursing and Pharmacy Students...
The Essentials of Biostatistics for Physicians, Nurses, and Clinicians
Biostatistics – Lecture Notes/Book (PDF) Nursing
Biostatistics are the development and application of statistical methods to a wide range of topics in biology. It encompasses the design of biological experiments, the collection and analysis of data from those experiments and the interpretation of the results.
Cochran-Mantel-Haenszel Test with Breslow-Day & Tarone CorrectionAzmi Mohd Tamil
This document discusses the Cochran-Mantel-Haenszel (CMH) method for adjusting odds ratios when analyzing the relationship between a dichotomous risk factor and outcome while controlling for potential confounding factors. It provides an example looking at the relationship between catecholamine levels (risk factor) and coronary heart disease (outcome) while adjusting for age and ECG changes (confounders). The CMH method is used to calculate stratum-specific odds ratios, an overall adjusted odds ratio of 1.89, and test for homogeneity across strata, finding no significant interaction between the risk factor and confounders.
The document discusses using a vector autoregression (VAR) model to forecast two time series - leads and binds - that interact with each other. A 5-period VAR model is found to best capture the weekly periodicity between the series. The model is shown to accurately forecast leads 1-11 days in advance, within 2% error, and binds within 5% error over a two week period, indicating the interaction between the series can be used to predict each going forward. Some conclusions drawn are that the VAR model performs well but could be improved by trying other techniques or adding external variables.
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Chapter 9: Inferences from Two Samples
9.3 Two Means, Two Dependent Samples, Matched Pairs
Answers to Data Analysis and interpretation modified 2020 (2410) (1).pptVanithadurai
1. The document provides examples and exercises for interpreting data from various epidemiological study designs, including cross-sectional studies, case-control studies, cohort studies, and randomized controlled trials.
2. Scenarios are presented analyzing prevalence, odds ratios, relative risks, confidence intervals, and p-values. Sample calculations are shown for measures of association and their precision.
3. The examples illustrate how to interpret findings and infer results to the overall population from studies examining hypertension, skin cancer risk from diuretic use, acute myocardial infarction risk from hypertension, and effect of iron-fortified salt on anemia.
The document discusses z-scores and how they can be used to compare scores on different tests or subjects. It provides the formula for calculating z-scores and examples of calculating z-scores from raw scores, means, and standard deviations. Practice problems are also included to demonstrate calculating z-scores.
Please Subscribe to this Channel for more solutions and lectures
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Chapter 9: Inferences from Two Samples
9.1: Inferences about Two Proportions
Analytics Project - Combined Cycle Power PlantJyothi Lakshmi
The document describes a dataset containing measurements collected from a combined cycle power plant over 6 years. The dataset contains 9568 hourly records of 4 ambient variables (temperature, exhaust vacuum, ambient pressure, relative humidity) and the corresponding electrical energy output. The records are split into training and test datasets. Exploratory data analysis finds strong correlations between the energy output and temperature, vacuum, and pressure. A multiple linear regression model will be used to predict the energy output based on the 4 ambient variables.
This document discusses the normal distribution and related concepts. It begins with an introduction to the normal distribution and its properties. It then covers the probability density function and cumulative distribution function of the normal distribution. The rest of the document discusses key properties like the 68-95-99.7 rule, using the standard normal distribution, and how to determine if a data set follows a normal distribution including using a normal probability plot. Examples are provided throughout to illustrate the concepts.
The document discusses key concepts related to risk and return including:
- Normal distribution and how it relates to standard deviation and z-scores.
- How to calculate the minimum and maximum expected returns over 1, 2, and 3 standard deviations from the mean for a stock with an 8% mean return and 10% standard deviation.
- Formulas for calculating the probability of returns above or below certain levels for a stock with a given mean and standard deviation.
- Definitions of covariance and correlation as ways to measure co-movement between assets.
- Examples of calculating covariance using historical and probabilistic stock price data.
- An introduction to the concept of beta as a measure of systematic risk.
This document discusses the normal distribution and its applications. It provides examples of using the normal distribution to calculate probabilities related to human pregnancy length and hematocrit values. The normal distribution can model many medical variables that have a central peak, such as blood pressure, hematocrit levels, and heights. Strictly speaking, only continuous variables like height or hematocrit that can take any value can have a normal distribution, not discrete variables like blood group or eye color.
This document provides information on chi-square tests and other statistical tests for qualitative data analysis. It discusses the chi-square test for goodness of fit and independence. It also covers Fisher's exact test and McNemar's test. Examples are provided to illustrate chi-square calculations and how to determine statistical significance based on degrees of freedom and critical values. Assumptions and criteria for applying different tests are outlined.
This document defines and explains key statistical concepts including measures of central tendency (mean, median, mode), measures of dispersion (range, standard deviation), and properties of distributions (skewness, symmetry). It provides examples of calculating the mean, median, mode, and standard deviation. It also describes the empirical rule and how a certain percentage of values in a normal distribution fall within 1, 2, or 3 standard deviations of the mean.
ExcelR is a proud partner of Universiti Malaysia Saravak (UNIMAS), Malaysia’s 1st public University and ranked 8th top university in Malaysia and ranked among top 200th in Asian University Rankings 2017 by QS World University Rankings. Participants will be awarded Data Science international certification from UNIMAS.
Excelr is a Data Analytics training delivery partner for over 5 universities, namely IIM, ISB, BITS Pilani, UNIMAS and Woxen School of Business and 40 + premier educational institutions. All our Trainers are Data Analytics experts with 15+ Years of experience and they hail from IIT, ISB and IIM. Few of our trainers successfully completed their Phd in Data Analytics.
Excelr is the only organization that is partnered with UNIMAS (University Malaysia Sarawak) to provide Data analytics certification with global validation. Being one of the best data Analytics Institutes, our Data Analysts from IIT and ISB offer Data Analytics certification course .More than 400+ participants were successfully placed with top MNCs namely E&Y, Accenture, VMWare, Infosys, IBM etc…
ExcelR is a proud partner of Universiti Malaysia Saravak (UNIMAS), Malaysia’s 1st public University and ranked 8th top university in Malaysia and ranked among top 200th in Asian University Rankings 2017 by QS World University Rankings. Participants will be awarded Data Science international certification from UNIMAS.
ExcelR offers 160 hours classroom training on Business Analytics / Data Scientist / Data Analytics. We are considered as one of the best training institutes on Business Analytics in noida “Faculty and vast course agenda is our differentiator”. The training is conducted by alumni of premier institutions such as IIT & ISB who has extensive experience in the arena of analytics.
ExcelR offers 160 hours classroom training on Business Analytics / Data Scientist / Data Analytics. We are considered as one of the best training institutes on Business Analytics in pune. “Faculty and vast course agenda is our differentiator”. The training is conducted by alumni of premier institutions such as IIT & ISB who has extensive experience in the arena of analytics.
ExcelR offers 160 hours classroom training on Business Analytics / Data Scientist / Data Analytics. We are considered as one of the best training institutes on Business Analytics in pune “Faculty and vast course agenda is our differentiator”. The training is conducted by alumni of premier institutions such as IIT & ISB who has extensive experience in the arena of analytics.
Similar to Cochran Mantel Haenszel Test with Breslow-Day Test & Quadratic Equation (20)
Audiovisual and technicalities from preparation to retrieval how to enhance m...Azmi Mohd Tamil
This document discusses strategies for enhancing online presentations for the Clinical Pathology Conference (CPC) at Universiti Kebangsaan Malaysia. It outlines the transition from initially streaming CPC sessions publicly on Facebook to creating a private Facebook group and YouTube channel to cater to different audiences. Equipment was purchased, including an HDMI encoder and later integrating direct streaming from Zoom. A future goal is to integrate hybrid sessions for the Grand CPC with a limited live audience and online participation. Recommendations are provided for achieving broadcast quality, including ensuring a stable internet connection and using a green screen to integrate presenters into slides.
Broadcast quality online teaching at zero budgetAzmi Mohd Tamil
1. The document discusses how to achieve broadcast quality for online teaching with zero budget by using free software like OBS Studio.
2. It provides step-by-step instructions on setting up OBS Studio scenes and configuring the software to live stream to platforms like Zoom, Teams, and Facebook.
3. Additional tips include using a green screen, selecting an optimal internet connection, and integrating graphics while streaming to enhance the online teaching experience without spending money on dedicated hardware.
This document provides instructions on how to use OBS Studio, a free and open-source software, for recording and streaming online lectures and events. It demonstrates how to configure scenes in OBS Studio with elements like webcam, background, and scrolling text. It also shows how to set up a virtual camera in OBS Studio to broadcast the video feed into platforms like Zoom, Teams, and Meet. Additionally, it discusses using green screen capabilities in OBS Studio to integrate separate media sources. Finally, it provides steps on streaming recordings directly to platforms like YouTube and Facebook.
Bengkel 21-12-2020 - Etika atas Talian & Alat MinimaAzmi Mohd Tamil
1. The document discusses equipment and software for achieving broadcast quality when teaching online, including a stable internet connection, using OBS Studio to customize video feeds on Zoom or Teams, and using a green screen.
2. It demonstrates how to configure OBS Studio scenes and layers, and how to stream to Facebook Live using the stream key.
3. It concludes that good quality online teaching is possible with a budget of EUR5 using a notebook, OBS Studio, and workarounds for internet access, rather than spending RM7600.
1) Blended learning, which combines online and face-to-face instruction, is now required for 50% of courses in Malaysian public universities by the Ministry of Higher Education.
2) Lecturers must upload certain minimum required materials to the UKMfolio online platform, including course synopses, at least 7 content files, 4 discussion activities, and 2 assessments.
3) The document provides an example of how one lecturer structured their course on the UKMfolio platform to meet these requirements by uploading files, creating discussions, and linking to external assessments via web tools.
The document discusses recoding variables in an SPSS data file to conduct statistical tests. It describes computing BMI from height and weight variables, then recoding BMI into categories of underweight, normal, and overweight. The recoding is done to test for associations between weight classification and the outcome of small for gestational age (SGA) babies. Steps shown include using the compute variable and recode functions in SPSS to generate new variables for weight classification based on BMI.
Introduction to Data Analysis With R and R StudioAzmi Mohd Tamil
- A study analyzed factors that can cause babies to be small for gestational age (SGA), including mothers' body mass index (BMI).
- The document discusses computing BMI from height and weight data, classifying BMI into underweight, normal, and overweight categories, and performing statistical tests to analyze associations between these factors and birthweight and SGA outcomes.
- Statistical tests discussed include chi-square tests, t-tests, ANOVA, and linear regression to identify relationships between maternal BMI, weight classification, and baby's birthweight and risk of SGA.
Hack#38 - How to Stream Zoom to Facebook & YouTube Without Using An Encoder o...Azmi Mohd Tamil
This document provides instructions for streaming Zoom or Microsoft Teams meetings to Facebook or YouTube without using an encoder or paid webinar package. It describes using the free software OBS Studio along with a VB-Cable to route audio and video between the video conferencing software and OBS. OBS Studio is then configured to stream the combined feed to platforms like Facebook Live. Steps covered include installing OBS Studio, the virtual camera plugin, VB-Cable and configuring the audio and video routes between the apps.
Hack#37 - How to simultaneously live stream to 4 sites using a single hardwar...Azmi Mohd Tamil
The document discusses how to simultaneously live stream to 4 sites using a single hardware encoder. It recommends the URayTech HDMI Video Streaming Encoder, which costs $121.50. It provides step-by-step instructions on configuring the encoder to stream to a Facebook page, Facebook group, and YouTube channel. While it mentions setting up a fourth stream, it is only able to demonstrate streaming to three platforms due to limitations of the encoder.
The document discusses assembling a Raspberry Pi 4 mini computer. It lists the components acquired: a Raspberry Pi 4 Model B 4GB, 7-inch touch screen display, touch screen interface, and power supply. It describes installing the operating system by downloading Raspbian or NOOBS, using Etcher to flash the OS to the microSD card, and inserting it into the Raspberry Pi 4. Setup involves enabling WiFi, selecting the OS, language and keyboard, then waiting for installation to finish. Once updated, the Raspberry Pi can be used like a PC to explore its capabilities.
This document discusses using a video encoder to stream Facebook Live broadcasts seamlessly between applications. It recommends buying an Epiphan Video Pearl 2 encoder but suggests a cheaper alternative that can be found on AliExpress. The setup involves connecting the presenter's PC via HDMI to the encoder, which is then connected via USB to a separate Facebook Live streaming PC. OBS Studio is installed on the streaming PC to access the encoder's video feed and configure the Facebook Live stream key and settings to begin broadcasting.
Hack#34 - Online Teaching with Microsoft TeamsAzmi Mohd Tamil
The document discusses how Microsoft Teams can be used for teaching. It notes that Teams allows teachers to email lesson links to students, invite students to Teams, and start teleconferences through the video symbol. Teachers can also add many apps like Zoom to Teams. The document recommends Teams as a platform for online teaching and learning.
This document provides instructions for going live on Facebook using Facebook Live. It details how to install the required Chrome extension to share your screen. It explains how to select your audience and choose whether to use a hardware encoder or built-in webcam to share your screen or app window. The steps are outlined, including going to the publishing tools on a Facebook page, selecting the audience, clicking "Go Live" and then stopping the share and saving the broadcast.
Skype for Business is available for all UKM staff and students through their Office 365 licenses, however some advanced features are not usable since UKM does not have an Exchange server. "Meet Now" can be used to create video conferences in Skype for Business and invite participants, but scheduling meetings through Outlook is not possible. Key features like file sharing and viewing the presenter's desktop are available once participants join the Skype meeting. In conclusion, while licensed for Skype for Business, UKM's lack of an Exchange server limits its functionality to the "Meet Now" option for video conferencing.
This document provides an introduction to structural equation modeling (SEM) through a series of definitions and explanations. It discusses key concepts in SEM including latent versus measured variables, covariance versus correlation, and the history and development of SEM. Sample size requirements and software for conducting SEM are also covered. The document is intended as introductory material for postgraduate students learning about SEM.
This document provides guidelines for protecting a personal computer from viruses, spyware, and hackers. It recommends installing and regularly updating antivirus and anti-spyware software such as ZoneAlarm, Outpost, Spybot Search & Destroy, and Ad-Aware. It also advises using Mozilla browser instead of Microsoft applications to avoid exploits, backing up data both on and off the computer, and being cautious of email attachments. The document emphasizes that education has improved with computers but proper security strategies are needed to prevent education impediments.
Introduction to 20 Classroom Hacks For Education 4.0 (updated)Azmi Mohd Tamil
This document provides an introduction to classroom hacks for Education 4.0 by Assoc. Prof. Dr. Azmi Mohd Tamil. It discusses how the audience and time for education is changing with more students accessing education remotely and increased use of technology. It introduces the concept of Education 4.0 in line with the Fourth Industrial Revolution, where learning will be less confined to physical classrooms and involve new pedagogies. While technologies offer opportunities, the document notes challenges in preparing teachers and adapting curricula to these changes. The workshop aims to provide quick educational hacks or techniques for utilizing different learning spaces, pedagogies, and technologies in teaching to help transition to Education 4.0.
This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.
Assessment and Planning in Educational technology.pptxKavitha Krishnan
In an education system, it is understood that assessment is only for the students, but on the other hand, the Assessment of teachers is also an important aspect of the education system that ensures teachers are providing high-quality instruction to students. The assessment process can be used to provide feedback and support for professional development, to inform decisions about teacher retention or promotion, or to evaluate teacher effectiveness for accountability purposes.
বাংলাদেশের অর্থনৈতিক সমীক্ষা ২০২৪ [Bangladesh Economic Review 2024 Bangla.pdf] কম্পিউটার , ট্যাব ও স্মার্ট ফোন ভার্সন সহ সম্পূর্ণ বাংলা ই-বুক বা pdf বই " সুচিপত্র ...বুকমার্ক মেনু 🔖 ও হাইপার লিংক মেনু 📝👆 যুক্ত ..
আমাদের সবার জন্য খুব খুব গুরুত্বপূর্ণ একটি বই ..বিসিএস, ব্যাংক, ইউনিভার্সিটি ভর্তি ও যে কোন প্রতিযোগিতা মূলক পরীক্ষার জন্য এর খুব ইম্পরট্যান্ট একটি বিষয় ...তাছাড়া বাংলাদেশের সাম্প্রতিক যে কোন ডাটা বা তথ্য এই বইতে পাবেন ...
তাই একজন নাগরিক হিসাবে এই তথ্য গুলো আপনার জানা প্রয়োজন ...।
বিসিএস ও ব্যাংক এর লিখিত পরীক্ষা ...+এছাড়া মাধ্যমিক ও উচ্চমাধ্যমিকের স্টুডেন্টদের জন্য অনেক কাজে আসবে ...
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...PECB
Denis is a dynamic and results-driven Chief Information Officer (CIO) with a distinguished career spanning information systems analysis and technical project management. With a proven track record of spearheading the design and delivery of cutting-edge Information Management solutions, he has consistently elevated business operations, streamlined reporting functions, and maximized process efficiency.
Certified as an ISO/IEC 27001: Information Security Management Systems (ISMS) Lead Implementer, Data Protection Officer, and Cyber Risks Analyst, Denis brings a heightened focus on data security, privacy, and cyber resilience to every endeavor.
His expertise extends across a diverse spectrum of reporting, database, and web development applications, underpinned by an exceptional grasp of data storage and virtualization technologies. His proficiency in application testing, database administration, and data cleansing ensures seamless execution of complex projects.
What sets Denis apart is his comprehensive understanding of Business and Systems Analysis technologies, honed through involvement in all phases of the Software Development Lifecycle (SDLC). From meticulous requirements gathering to precise analysis, innovative design, rigorous development, thorough testing, and successful implementation, he has consistently delivered exceptional results.
Throughout his career, he has taken on multifaceted roles, from leading technical project management teams to owning solutions that drive operational excellence. His conscientious and proactive approach is unwavering, whether he is working independently or collaboratively within a team. His ability to connect with colleagues on a personal level underscores his commitment to fostering a harmonious and productive workplace environment.
Date: May 29, 2024
Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
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Executive Directors Chat Leveraging AI for Diversity, Equity, and InclusionTechSoup
Let’s explore the intersection of technology and equity in the final session of our DEI series. Discover how AI tools, like ChatGPT, can be used to support and enhance your nonprofit's DEI initiatives. Participants will gain insights into practical AI applications and get tips for leveraging technology to advance their DEI goals.
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