SPSS.ppt
•Download as PPT, PDF•
0 likes•6 views
SPSS is a popular statistical software package used for data management and analysis. It allows users to perform complex calculations and analyses with simple commands. The default window contains a data editor with two views - the data view shows raw data while the variable view describes each variable. SPSS can analyze different scales of measurement like nominal, ordinal, interval, and ratio scales. Common analyses introduced include frequencies, descriptives to find averages and standard deviations, linear regression, t-tests to compare groups, and graphs to visualize results.
Report
Share
Report
Share
Recommended
Basics of SPSS and how to use it first time
SPSS is a popular statistical software package that allows users to perform complex data analysis with simple instructions. It displays data in a data editor with two views: the data view shows raw data while the variable view describes each variable. SPSS can analyze nominal, ordinal, interval, and ratio scales of measurement. Basic analyses introduced include frequencies, descriptives to calculate averages and standard deviations, linear regression, t-tests, and graphs like bar charts, pie charts, line charts and histograms. Users select analyses from menus, define variables and groups, and view automated output of statistical results.
Spss basic Dr Marwa Zalat
This document provides an overview of how to use SPSS to conduct basic statistical analysis and present results. It outlines expectations for the workshop, including learning how to prepare an SPSS file, display and summarize data, and create graphical presentations. The document then covers key SPSS concepts like variables, data types, and examples. It also demonstrates how to perform descriptive statistics, frequency tables, crosstabs, measures of central tendency and dispersion. Finally, it discusses different methods of graphical presentation in SPSS like bar charts, histograms, box plots and more.
mean comparison.pptx
The document provides information on statistical techniques for comparing means between groups, including t-tests, analysis of variance (ANOVA), and their assumptions and applications. T-tests are used to compare two groups, while ANOVA allows comparison of three or more groups and controls for increased Type I error rates. Steps for conducting t-tests, ANOVA, and post-hoc tests using SPSS are outlined along with examples and interpretations.
mean comparison.pptx
The document discusses statistical methods for comparing means between groups, including t-tests and analysis of variance (ANOVA). It provides information on different types of t-tests (one sample, independent samples, and paired samples t-tests), assumptions of t-tests, and how to perform t-tests in SPSS. It also covers one-way ANOVA, including its assumptions, components of variation, properties of the F-test, and how to run a one-way ANOVA in SPSS. Examples are provided for each statistical test.
univariate and bivariate analysis in spss
this slide will help to perform various tests in spss targeting univariate and bivariate analysis along with the way of entering and analyzing multiple responses.
5. testing differences
This document introduces difference testing and parametric and non-parametric tests. It discusses the assumptions of parametric tests including random sampling, normally distributed interval/ratio data, and equal variances. Non-parametric tests like Wilcoxon and Mann-Whitney U are introduced as alternatives. Key principles of difference testing like independent vs dependent variables are explained. Steps for t-tests, paired t-tests, and non-parametric equivalents are outlined along with interpreting SPSS outputs and dealing with issues of significance. Factors like meaningful vs statistical significance and one-tailed vs two-tailed tests are also briefly covered.
ANOVA 2023 aa 2564896.pptx
ANOVA (analysis of variance) allows researchers to compare the means of three or more groups. It partitions the total variation in the data into variation between groups and variation within groups. The ANOVA F-statistic is the ratio of between-group variation to within-group variation. A large F-statistic indicates the between-group variation is larger than expected by chance, providing evidence the group means are not all equal. Researchers can then follow up with post-hoc tests to determine which specific group means are different.
Anova lecture
The document discusses analysis of variance (ANOVA) which is used to compare the means of three or more groups. It explains that ANOVA avoids the problems of multiple t-tests by providing an omnibus test of differences between groups. The key steps of ANOVA are outlined, including partitioning variation between and within groups to calculate an F-ratio. A large F value indicates more difference between groups than expected by chance alone.
Recommended
Basics of SPSS and how to use it first time
SPSS is a popular statistical software package that allows users to perform complex data analysis with simple instructions. It displays data in a data editor with two views: the data view shows raw data while the variable view describes each variable. SPSS can analyze nominal, ordinal, interval, and ratio scales of measurement. Basic analyses introduced include frequencies, descriptives to calculate averages and standard deviations, linear regression, t-tests, and graphs like bar charts, pie charts, line charts and histograms. Users select analyses from menus, define variables and groups, and view automated output of statistical results.
Spss basic Dr Marwa Zalat
This document provides an overview of how to use SPSS to conduct basic statistical analysis and present results. It outlines expectations for the workshop, including learning how to prepare an SPSS file, display and summarize data, and create graphical presentations. The document then covers key SPSS concepts like variables, data types, and examples. It also demonstrates how to perform descriptive statistics, frequency tables, crosstabs, measures of central tendency and dispersion. Finally, it discusses different methods of graphical presentation in SPSS like bar charts, histograms, box plots and more.
mean comparison.pptx
The document provides information on statistical techniques for comparing means between groups, including t-tests, analysis of variance (ANOVA), and their assumptions and applications. T-tests are used to compare two groups, while ANOVA allows comparison of three or more groups and controls for increased Type I error rates. Steps for conducting t-tests, ANOVA, and post-hoc tests using SPSS are outlined along with examples and interpretations.
mean comparison.pptx
The document discusses statistical methods for comparing means between groups, including t-tests and analysis of variance (ANOVA). It provides information on different types of t-tests (one sample, independent samples, and paired samples t-tests), assumptions of t-tests, and how to perform t-tests in SPSS. It also covers one-way ANOVA, including its assumptions, components of variation, properties of the F-test, and how to run a one-way ANOVA in SPSS. Examples are provided for each statistical test.
univariate and bivariate analysis in spss
this slide will help to perform various tests in spss targeting univariate and bivariate analysis along with the way of entering and analyzing multiple responses.
5. testing differences
This document introduces difference testing and parametric and non-parametric tests. It discusses the assumptions of parametric tests including random sampling, normally distributed interval/ratio data, and equal variances. Non-parametric tests like Wilcoxon and Mann-Whitney U are introduced as alternatives. Key principles of difference testing like independent vs dependent variables are explained. Steps for t-tests, paired t-tests, and non-parametric equivalents are outlined along with interpreting SPSS outputs and dealing with issues of significance. Factors like meaningful vs statistical significance and one-tailed vs two-tailed tests are also briefly covered.
ANOVA 2023 aa 2564896.pptx
ANOVA (analysis of variance) allows researchers to compare the means of three or more groups. It partitions the total variation in the data into variation between groups and variation within groups. The ANOVA F-statistic is the ratio of between-group variation to within-group variation. A large F-statistic indicates the between-group variation is larger than expected by chance, providing evidence the group means are not all equal. Researchers can then follow up with post-hoc tests to determine which specific group means are different.
Anova lecture
The document discusses analysis of variance (ANOVA) which is used to compare the means of three or more groups. It explains that ANOVA avoids the problems of multiple t-tests by providing an omnibus test of differences between groups. The key steps of ANOVA are outlined, including partitioning variation between and within groups to calculate an F-ratio. A large F value indicates more difference between groups than expected by chance alone.
1. complete stats notes
1) Statistics is the science of collecting, analyzing, and drawing conclusions from data. It is used to understand populations based on samples since directly measuring entire populations is often impossible.
2) There are two main types of data: qualitative data which relates to descriptive characteristics, and quantitative data which can be expressed numerically. Common statistical analyses include calculating the mean, standard deviation, and using t-tests, ANOVA, correlation, and chi-squared tests.
3) Statistical analyses allow researchers to determine uncertainties in measurements, compare groups, identify relationships between variables, and assess whether observed differences are likely due to chance or a factor being studied. Key concepts include null and alternative hypotheses, p-values, and effect size.
Inferential statistics quantitative data - single sample and 2 groups
This document provides an overview of inferential statistics concepts including probability, normal and t-distributions, hypothesis testing, and common statistical tests such as the t-test, Mann-Whitney U test, and single sample t-test. It discusses assumptions and procedures for conducting parametric and non-parametric statistical tests in SPSS and GraphPad Prism software. Key points covered include central limit theorem, hypothesis testing using confidence intervals and cumulative distribution functions, and choosing appropriate tests based on sample size and normality of data distribution.
Statistics for Anaesthesiologists
Statistics for Anaesthesiologists covers basic to intermediate level statistics for researchers especially commonly used study designs or tests in Anaesthesiology research.
Discriminant analysis
This summary analyzes a document describing the use of discriminant analysis in SPSS to predict whether graduate students will successfully complete their PhD programs based on information collected before acceptance. It identifies key outputs of the discriminant analysis including tests showing one predictor variable significantly differs between groups, coefficients of the discriminant function, group centroids, and a classification results table showing around 80% of students were correctly classified.
Testing of hypothesis.pptx
This document discusses different types of t-tests used for hypothesis testing, including the independent samples t-test, paired samples t-test, and one sample t-test. It provides examples and steps for performing each test in SPSS. The independent samples t-test is used to compare the means of two independent groups, the paired samples t-test compares means from the same subjects under two conditions, and the one sample t-test tests if a sample mean differs from a hypothesized population mean. Assumptions for each test include normality, independence of observations, and no outliers.
T test, independant sample, paired sample and anova
The document discusses various statistical analyses that can be performed in SPSS, including t-tests, ANOVA, and post-hoc tests. It provides details on one-sample t-tests, independent t-tests, paired t-tests, one-way ANOVA tests, and evaluating assumptions like normality. Examples are given on how to conduct these tests in SPSS and how to interpret the output. Guidance is provided on follow-up post-hoc tests that can be used after ANOVA to examine differences between specific groups.
Unit-5.-t-test.ppt
This document provides information about independent samples t-tests and dependent/paired samples t-tests. It explains that independent samples t-tests are used to compare two independent groups, while dependent samples t-tests are used to compare observations within a single group. The key steps for each test are outlined, including stating hypotheses, calculating the test statistic, determining critical values, and making conclusions. Examples are provided to demonstrate how to perform the tests by hand and using SPSS.
Basics of Stats (2).pptx
This document provides an overview of basic statistics concepts including descriptive statistics, measures of central tendency, variability, sampling, and distributions. It defines key terms like mean, median, mode, range, standard deviation, variance, and quantiles. Examples are provided to demonstrate how to calculate and interpret these common statistical measures.
Univariate analysis:Medical statistics Part IV
Univariate analysis examines one variable at a time across a sample. There are three main tools used in univariate analysis: distribution of frequency, measures of central tendency (mean, median, mode), and measures of dispersion. Distribution examines individual values, range, and charts. Central tendency measures the average or middle value. Dispersion measures the spread around the central tendency, such as the standard deviation and range. Common univariate analysis procedures include frequencies, descriptives, and explore in SPSS.
Factorial Experiments
This document discusses strategies for designing factorial experiments with multiple factors. It explains that factorial experiments involve studying the effect of varying levels of factors on a response variable. The optimal design strategy depends on whether the circumstances are unusual or normal. For normal circumstances where there is some noise and factors influence each other, a fractional factorial or full factorial design is typically best. The document provides details on analyzing the data from factorial experiments to determine if factor effects and interactions are significant. It includes examples of calculating main effects and interactions from 2-level factorial data.
Sampling of Blood
This document discusses key concepts related to sampling and measurement in research. It covers topics such as population and sampling criteria when selecting a sample. It also discusses levels of measurement, reliability, validity, and different measurement strategies like interviews, questionnaires, and scales. Finally, it provides an overview of statistical analysis, including descriptive statistics, levels of measurement, and common statistical tests. The overall purpose is to introduce fundamental concepts for designing research studies and analyzing quantitative data.
Back to the basics-Part2: Data exploration: representing and testing data pro...
This document discusses exploring and representing data properties through statistical analysis techniques. It covers topics like descriptive statistics, graphical representations of data through histograms and boxplots, testing for normality and homogeneity of variance, and exploring differences between groups of data. The goal is to properly examine data distributions and assumptions before conducting further statistical tests and analysis.
Inferential statistics
The document provides an overview of inferential statistics. It defines inferential statistics as making generalizations about a larger population based on a sample. Key topics covered include hypothesis testing, types of hypotheses, significance tests, critical values, p-values, confidence intervals, z-tests, t-tests, ANOVA, chi-square tests, correlation, and linear regression. The document aims to explain these statistical concepts and techniques at a high level.
CABT Math 8 measures of central tendency and dispersion
This document provides an introduction to statistics. It discusses what statistics is, the two main branches of statistics (descriptive and inferential), and the different types of data. It then describes several key measures used in statistics, including measures of central tendency (mean, median, mode) and measures of dispersion (range, mean deviation, standard deviation). The mean is the average value, the median is the middle value, and the mode is the most frequent value. The range is the difference between highest and lowest values, the mean deviation is the average distance from the mean, and the standard deviation measures how spread out values are from the mean. Examples are provided to demonstrate how to calculate each measure.
inferentialstatistics-210411214248.pdf
This document provides an overview of inferential statistics. It defines inferential statistics as using data to make generalizations about a larger population beyond the available sample data. Key points include:
- Inferential statistics uses hypothesis testing and estimation to analyze data. It involves making inferences about a population from a sample.
- Hypothesis testing involves forming a null and alternative hypothesis, setting a significance level, choosing a statistical test, and making a decision to accept or reject the null hypothesis based on the p-value or critical value.
- Estimation provides point estimates and interval estimates like confidence intervals to describe population parameters based on sample data.
- Common inferential statistical tests covered are z-tests, t
Applied statistics lecture_3
This document provides an introduction to applied statistics and statistical methods. It discusses objectives such as going beyond the mean and tests of differences like t-tests and ANOVA. It also covers descriptive statistics such as measures of central tendency and dispersion, inferential statistics like z-scores and confidence intervals, and tests of differences including independent and paired t-tests and nonparametric alternatives.
Week 5 Independent t Test ExercisesPart IThe hypothesis bein.docx
Week 5 Independent t Test Exercises
Part I
The hypothesis being tested is: Women who are working will have a lower level of depression as compared to women who are not working.
Using Polit2SetC SPSS dataset, which contains a number of mental health variables, determine if the above hypothesis is true.
Follow these steps when using SPSS:
Open Polit2SetC dataset.
Click Analyze then click Compare Means, then Independent Sample T-test.
Move the Dependent Variable (CES_D Score “cesd”) in the area labelled Test Variable.
Move the Independent Variable (Currently Employed “worknow”) into the area labelled Grouping Variable. The worknow variable is coded as (0= those women who do not work and 1= those women who are working). Click on Define Groups in group 1 box type 0 and in group 2 box type 1. Click Continue.
Click continue and then click OK.
Assignment: Through analysis of the data and use of the questions below write one to two paragraphs summarizing your findings from this t-test.
How many women were employed versus not employed in the sample?
What is the total sample size?
What are the mean (SD) CES-D scores for each group?
Interpret the Levene’s statistic. (Hint: Is the assumption of homogeneity of variance met? Are equal variances assumed or not assumed?)
What is the value of the t-statistic, number of degrees of freedom and the p-value?
Does the data support the hypothesis? Why or why not?
Part II
Hypothesis: Women who reported depression scores in wave 1 and wave 2 of the study did not have a significant difference in their level of depression.
Using Polit2SetC SPSS dataset, determine if the above hypothesis is true.
Follow these steps when using SPSS:
Open Polit2SetC dataset.
Click Analyze then click Compare Means, then Paired Samples T-test.
First click on CES-D Score (cesd) and move it into the box labelled Paired Variables (in the rectangle for Pair 1 of Variable 1 and then click on CESD Score, Wave 1 (cesdwav1) and move it into the Paired Variables box (in the rectangle next to CES-D Score, pair 1, variable 2).
Click continue and then click OK.
Assignment: Through analysis of the data and use of the questions below write one to two paragraphs summarizing your findings from this t-test.
What is the total sample size?
What are the mean (SD) CES-D scores at wave 1 and wave 2?
What is the mean difference between the two time periods?
What is the value of the t-statistic, number of degrees of freedom and the p-value(sig)?
Does the data support the hypothesis? Why or why not?
Part III
Using Polit2SetC dataset, run independent groups t-tests for three outcomes. The outcome variables are CES-D Score (cesd), SF12: Physical Health Component Score, standardized (sf12phys) and SF12: Mental Health Component Score, standardized (sf12ment).
Follow these steps when using SPSS:
Open Polit2SetC dataset.
Click Analyze then click Compare Means, then Independent Sample T-test.
Move the Dependent Variables (.
scope and need of biostatics
This powerpoint presentation gives a brief explanation about the biostatic data .this is quite helpful to individuals to understand the basic research methodology terminologys
Univariate, bivariate analysis, hypothesis testing, chi square
This document provides an introduction to data analysis. It discusses various topics related to measurement and types of data, including univariate and bivariate analysis. For univariate analysis, it describes descriptive statistics such as mean, median, mode, variance, and standard deviation. It also discusses data distributions and different measurement scales. For bivariate analysis, it introduces cross-tabulation and chi-square tests to examine relationships between two variables. Cross-tabulation allows looking at associations between variables through frequencies and percentages in tables, while chi-square can be used to test hypotheses about relationships and determine statistical significance.
Data analysis
The document discusses different measures of central tendency (mean, median, mode) and how to determine which is most appropriate based on the type of data. It also covers measures of dispersion like range, standard deviation, and variance which provide information about how spread out values are from the central point. The mean is the most commonly used measure of central tendency but the median is less affected by outliers, while the mode represents the most frequent value.
Experts live - Improving user adoption with AI
Bekijk de slides van onze sessie Enhancing Modern Workplace Efficiency op Experts Live 2024.
一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理
毕业原版【微信:176555708】【(GWU,GW毕业证书)乔治·华盛顿大学毕业证】【微信:176555708】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信176555708】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信176555708】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
More Related Content
Similar to SPSS.ppt
1. complete stats notes
1) Statistics is the science of collecting, analyzing, and drawing conclusions from data. It is used to understand populations based on samples since directly measuring entire populations is often impossible.
2) There are two main types of data: qualitative data which relates to descriptive characteristics, and quantitative data which can be expressed numerically. Common statistical analyses include calculating the mean, standard deviation, and using t-tests, ANOVA, correlation, and chi-squared tests.
3) Statistical analyses allow researchers to determine uncertainties in measurements, compare groups, identify relationships between variables, and assess whether observed differences are likely due to chance or a factor being studied. Key concepts include null and alternative hypotheses, p-values, and effect size.
Inferential statistics quantitative data - single sample and 2 groups
This document provides an overview of inferential statistics concepts including probability, normal and t-distributions, hypothesis testing, and common statistical tests such as the t-test, Mann-Whitney U test, and single sample t-test. It discusses assumptions and procedures for conducting parametric and non-parametric statistical tests in SPSS and GraphPad Prism software. Key points covered include central limit theorem, hypothesis testing using confidence intervals and cumulative distribution functions, and choosing appropriate tests based on sample size and normality of data distribution.
Statistics for Anaesthesiologists
Statistics for Anaesthesiologists covers basic to intermediate level statistics for researchers especially commonly used study designs or tests in Anaesthesiology research.
Discriminant analysis
This summary analyzes a document describing the use of discriminant analysis in SPSS to predict whether graduate students will successfully complete their PhD programs based on information collected before acceptance. It identifies key outputs of the discriminant analysis including tests showing one predictor variable significantly differs between groups, coefficients of the discriminant function, group centroids, and a classification results table showing around 80% of students were correctly classified.
Testing of hypothesis.pptx
This document discusses different types of t-tests used for hypothesis testing, including the independent samples t-test, paired samples t-test, and one sample t-test. It provides examples and steps for performing each test in SPSS. The independent samples t-test is used to compare the means of two independent groups, the paired samples t-test compares means from the same subjects under two conditions, and the one sample t-test tests if a sample mean differs from a hypothesized population mean. Assumptions for each test include normality, independence of observations, and no outliers.
T test, independant sample, paired sample and anova
The document discusses various statistical analyses that can be performed in SPSS, including t-tests, ANOVA, and post-hoc tests. It provides details on one-sample t-tests, independent t-tests, paired t-tests, one-way ANOVA tests, and evaluating assumptions like normality. Examples are given on how to conduct these tests in SPSS and how to interpret the output. Guidance is provided on follow-up post-hoc tests that can be used after ANOVA to examine differences between specific groups.
Unit-5.-t-test.ppt
This document provides information about independent samples t-tests and dependent/paired samples t-tests. It explains that independent samples t-tests are used to compare two independent groups, while dependent samples t-tests are used to compare observations within a single group. The key steps for each test are outlined, including stating hypotheses, calculating the test statistic, determining critical values, and making conclusions. Examples are provided to demonstrate how to perform the tests by hand and using SPSS.
Basics of Stats (2).pptx
This document provides an overview of basic statistics concepts including descriptive statistics, measures of central tendency, variability, sampling, and distributions. It defines key terms like mean, median, mode, range, standard deviation, variance, and quantiles. Examples are provided to demonstrate how to calculate and interpret these common statistical measures.
Univariate analysis:Medical statistics Part IV
Univariate analysis examines one variable at a time across a sample. There are three main tools used in univariate analysis: distribution of frequency, measures of central tendency (mean, median, mode), and measures of dispersion. Distribution examines individual values, range, and charts. Central tendency measures the average or middle value. Dispersion measures the spread around the central tendency, such as the standard deviation and range. Common univariate analysis procedures include frequencies, descriptives, and explore in SPSS.
Factorial Experiments
This document discusses strategies for designing factorial experiments with multiple factors. It explains that factorial experiments involve studying the effect of varying levels of factors on a response variable. The optimal design strategy depends on whether the circumstances are unusual or normal. For normal circumstances where there is some noise and factors influence each other, a fractional factorial or full factorial design is typically best. The document provides details on analyzing the data from factorial experiments to determine if factor effects and interactions are significant. It includes examples of calculating main effects and interactions from 2-level factorial data.
Sampling of Blood
This document discusses key concepts related to sampling and measurement in research. It covers topics such as population and sampling criteria when selecting a sample. It also discusses levels of measurement, reliability, validity, and different measurement strategies like interviews, questionnaires, and scales. Finally, it provides an overview of statistical analysis, including descriptive statistics, levels of measurement, and common statistical tests. The overall purpose is to introduce fundamental concepts for designing research studies and analyzing quantitative data.
Back to the basics-Part2: Data exploration: representing and testing data pro...
This document discusses exploring and representing data properties through statistical analysis techniques. It covers topics like descriptive statistics, graphical representations of data through histograms and boxplots, testing for normality and homogeneity of variance, and exploring differences between groups of data. The goal is to properly examine data distributions and assumptions before conducting further statistical tests and analysis.
Inferential statistics
The document provides an overview of inferential statistics. It defines inferential statistics as making generalizations about a larger population based on a sample. Key topics covered include hypothesis testing, types of hypotheses, significance tests, critical values, p-values, confidence intervals, z-tests, t-tests, ANOVA, chi-square tests, correlation, and linear regression. The document aims to explain these statistical concepts and techniques at a high level.
CABT Math 8 measures of central tendency and dispersion
This document provides an introduction to statistics. It discusses what statistics is, the two main branches of statistics (descriptive and inferential), and the different types of data. It then describes several key measures used in statistics, including measures of central tendency (mean, median, mode) and measures of dispersion (range, mean deviation, standard deviation). The mean is the average value, the median is the middle value, and the mode is the most frequent value. The range is the difference between highest and lowest values, the mean deviation is the average distance from the mean, and the standard deviation measures how spread out values are from the mean. Examples are provided to demonstrate how to calculate each measure.
inferentialstatistics-210411214248.pdf
This document provides an overview of inferential statistics. It defines inferential statistics as using data to make generalizations about a larger population beyond the available sample data. Key points include:
- Inferential statistics uses hypothesis testing and estimation to analyze data. It involves making inferences about a population from a sample.
- Hypothesis testing involves forming a null and alternative hypothesis, setting a significance level, choosing a statistical test, and making a decision to accept or reject the null hypothesis based on the p-value or critical value.
- Estimation provides point estimates and interval estimates like confidence intervals to describe population parameters based on sample data.
- Common inferential statistical tests covered are z-tests, t
Applied statistics lecture_3
This document provides an introduction to applied statistics and statistical methods. It discusses objectives such as going beyond the mean and tests of differences like t-tests and ANOVA. It also covers descriptive statistics such as measures of central tendency and dispersion, inferential statistics like z-scores and confidence intervals, and tests of differences including independent and paired t-tests and nonparametric alternatives.
Week 5 Independent t Test ExercisesPart IThe hypothesis bein.docx
Week 5 Independent t Test Exercises
Part I
The hypothesis being tested is: Women who are working will have a lower level of depression as compared to women who are not working.
Using Polit2SetC SPSS dataset, which contains a number of mental health variables, determine if the above hypothesis is true.
Follow these steps when using SPSS:
Open Polit2SetC dataset.
Click Analyze then click Compare Means, then Independent Sample T-test.
Move the Dependent Variable (CES_D Score “cesd”) in the area labelled Test Variable.
Move the Independent Variable (Currently Employed “worknow”) into the area labelled Grouping Variable. The worknow variable is coded as (0= those women who do not work and 1= those women who are working). Click on Define Groups in group 1 box type 0 and in group 2 box type 1. Click Continue.
Click continue and then click OK.
Assignment: Through analysis of the data and use of the questions below write one to two paragraphs summarizing your findings from this t-test.
How many women were employed versus not employed in the sample?
What is the total sample size?
What are the mean (SD) CES-D scores for each group?
Interpret the Levene’s statistic. (Hint: Is the assumption of homogeneity of variance met? Are equal variances assumed or not assumed?)
What is the value of the t-statistic, number of degrees of freedom and the p-value?
Does the data support the hypothesis? Why or why not?
Part II
Hypothesis: Women who reported depression scores in wave 1 and wave 2 of the study did not have a significant difference in their level of depression.
Using Polit2SetC SPSS dataset, determine if the above hypothesis is true.
Follow these steps when using SPSS:
Open Polit2SetC dataset.
Click Analyze then click Compare Means, then Paired Samples T-test.
First click on CES-D Score (cesd) and move it into the box labelled Paired Variables (in the rectangle for Pair 1 of Variable 1 and then click on CESD Score, Wave 1 (cesdwav1) and move it into the Paired Variables box (in the rectangle next to CES-D Score, pair 1, variable 2).
Click continue and then click OK.
Assignment: Through analysis of the data and use of the questions below write one to two paragraphs summarizing your findings from this t-test.
What is the total sample size?
What are the mean (SD) CES-D scores at wave 1 and wave 2?
What is the mean difference between the two time periods?
What is the value of the t-statistic, number of degrees of freedom and the p-value(sig)?
Does the data support the hypothesis? Why or why not?
Part III
Using Polit2SetC dataset, run independent groups t-tests for three outcomes. The outcome variables are CES-D Score (cesd), SF12: Physical Health Component Score, standardized (sf12phys) and SF12: Mental Health Component Score, standardized (sf12ment).
Follow these steps when using SPSS:
Open Polit2SetC dataset.
Click Analyze then click Compare Means, then Independent Sample T-test.
Move the Dependent Variables (.
scope and need of biostatics
This powerpoint presentation gives a brief explanation about the biostatic data .this is quite helpful to individuals to understand the basic research methodology terminologys
Univariate, bivariate analysis, hypothesis testing, chi square
This document provides an introduction to data analysis. It discusses various topics related to measurement and types of data, including univariate and bivariate analysis. For univariate analysis, it describes descriptive statistics such as mean, median, mode, variance, and standard deviation. It also discusses data distributions and different measurement scales. For bivariate analysis, it introduces cross-tabulation and chi-square tests to examine relationships between two variables. Cross-tabulation allows looking at associations between variables through frequencies and percentages in tables, while chi-square can be used to test hypotheses about relationships and determine statistical significance.
Data analysis
The document discusses different measures of central tendency (mean, median, mode) and how to determine which is most appropriate based on the type of data. It also covers measures of dispersion like range, standard deviation, and variance which provide information about how spread out values are from the central point. The mean is the most commonly used measure of central tendency but the median is less affected by outliers, while the mode represents the most frequent value.
Similar to SPSS.ppt (20)
Inferential statistics quantitative data - single sample and 2 groups
Inferential statistics quantitative data - single sample and 2 groups
T test, independant sample, paired sample and anova
T test, independant sample, paired sample and anova
Back to the basics-Part2: Data exploration: representing and testing data pro...
Back to the basics-Part2: Data exploration: representing and testing data pro...
CABT Math 8 measures of central tendency and dispersion
CABT Math 8 measures of central tendency and dispersion
Week 5 Independent t Test ExercisesPart IThe hypothesis bein.docx
Week 5 Independent t Test ExercisesPart IThe hypothesis bein.docx
Univariate, bivariate analysis, hypothesis testing, chi square
Univariate, bivariate analysis, hypothesis testing, chi square
Recently uploaded
Experts live - Improving user adoption with AI
Bekijk de slides van onze sessie Enhancing Modern Workplace Efficiency op Experts Live 2024.
一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理
毕业原版【微信:176555708】【(GWU,GW毕业证书)乔治·华盛顿大学毕业证】【微信:176555708】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信176555708】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信176555708】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
一比一原版英属哥伦比亚大学毕业证(UBC毕业证书)学历如何办理
原版办【微信号:BYZS866】【英属哥伦比亚大学毕业证(UBC毕业证书)】【微信号:BYZS866】《成绩单、外壳、雅思、offer、真实留信官方学历认证（永久存档/真实可查）》采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路）我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信号BYZS866】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信号BYZS866】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
一比一原版南十字星大学毕业证(SCU毕业证书)学历如何办理
原版办理【微信号:BYZS866】【南十字星大学毕业证(SCU毕业证书)】【微信号:BYZS866】《成绩单、外壳、雅思、offer、真实留信官方学历认证（永久存档/真实可查）》采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路）我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信号BYZS866】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信号BYZS866】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
End-to-end pipeline agility - Berlin Buzzwords 2024
We describe how we achieve high change agility in data engineering by eliminating the fear of breaking downstream data pipelines through end-to-end pipeline testing, and by using schema metaprogramming to safely eliminate boilerplate involved in changes that affect whole pipelines.
A quick poll on agility in changing pipelines from end to end indicated a huge span in capabilities. For the question "How long time does it take for all downstream pipelines to be adapted to an upstream change," the median response was 6 months, but some respondents could do it in less than a day. When quantitative data engineering differences between the best and worst are measured, the span is often 100x-1000x, sometimes even more.
A long time ago, we suffered at Spotify from fear of changing pipelines due to not knowing what the impact might be downstream. We made plans for a technical solution to test pipelines end-to-end to mitigate that fear, but the effort failed for cultural reasons. We eventually solved this challenge, but in a different context. In this presentation we will describe how we test full pipelines effectively by manipulating workflow orchestration, which enables us to make changes in pipelines without fear of breaking downstream.
Making schema changes that affect many jobs also involves a lot of toil and boilerplate. Using schema-on-read mitigates some of it, but has drawbacks since it makes it more difficult to detect errors early. We will describe how we have rejected this tradeoff by applying schema metaprogramming, eliminating boilerplate but keeping the protection of static typing, thereby further improving agility to quickly modify data pipelines without fear.
"Financial Odyssey: Navigating Past Performance Through Diverse Analytical Lens"
Embark on a captivating financial journey with 'Financial Odyssey,' our hackathon project. Delve deep into the past performance of two companies as we employ an array of financial statement analysis techniques. From ratio analysis to trend analysis, uncover insights crucial for informed decision-making in the dynamic world of finance."
一比一原版巴斯大学毕业证(Bath毕业证书)学历如何办理
原版办理【微信号:BYZS866】【巴斯大学毕业证(Bath毕业证书)】【微信号:BYZS866】《成绩单、外壳、雅思、offer、真实留信官方学历认证（永久存档/真实可查）》采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【关于学历材料质量】
我们承诺采用的是学校原版纸张（原版纸质、底色、纹路、）我们工厂拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有成品以及工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信号BYZS866】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信号BYZS866】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样
学校原件一模一样【微信：741003700 】《(unimelb毕业证书)墨尔本大学毕业证》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
一比一原版(harvard毕业证书）哈佛大学毕业证如何办理
一模一样【微信：A575476】【(harvard毕业证书）哈佛大学毕业证成绩单Offer】【微信：A575476】（留信学历认证永久存档查询）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信：A575476】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信：A575476】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
→ 【关于价格问题（保证一手价格）
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：可来公司面谈，可签订合同，会陪同客户一起到教育部认证窗口递交认证材料，客户在教育部官方认证查询网站查询到认证通过结果后付款，不成功不收费！
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
by
Timothy Spann
Principal Developer Advocate
https://budapestdata.hu/2024/en/
https://budapestml.hu/2024/en/
tim.spann@zilliz.com
https://www.linkedin.com/in/timothyspann/
https://x.com/paasdev
https://github.com/tspannhw
https://www.youtube.com/@flank-stack
milvus
vector database
gen ai
generative ai
deep learning
machine learning
apache nifi
apache pulsar
apache kafka
apache flink
在线办理(英国UCA毕业证书)创意艺术大学毕业证在读证明一模一样
学校原件一模一样【微信：741003700 】《(英国UCA毕业证书)创意艺术大学毕业证》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
The Ipsos - AI - Monitor 2024 Report.pdf
According to Ipsos AI Monitor's 2024 report, 65% Indians said that products and services using AI have profoundly changed their daily life in the past 3-5 years.
一比一原版兰加拉学院毕业证(Langara毕业证书)学历如何办理
原版办【微信号:BYZS866】【兰加拉学院毕业证(Langara毕业证书)】【微信号:BYZS866】《成绩单、外壳、雅思、offer、真实留信官方学历认证（永久存档/真实可查）》采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路）我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信号BYZS866】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信号BYZS866】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
一比一原版(CU毕业证)卡尔顿大学毕业证如何办理
原件一模一样【微信：95270640】【卡尔顿大学毕业证CU学位证成绩单】【微信：95270640】（留信学历认证永久存档查询）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信：95270640】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信：95270640】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份【微信：95270640】
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
→ 【关于价格问题（保证一手价格）
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：可来公司面谈，可签订合同，会陪同客户一起到教育部认证窗口递交认证材料，客户在教育部官方认证查询网站查询到认证通过结果后付款，不成功不收费！
办理卡尔顿大学毕业证本科学位证成绩单CU学位证【微信：95270640 】外观非常精致，由特殊纸质材料制成，上面印有校徽、校名、毕业生姓名、专业等信息。
办理卡尔顿大学毕业证CU学位证本科学位证成绩单【微信：95270640 】格式相对统一，各专业都有相应的模板。通常包括以下部分：
校徽：象征着学校的荣誉和传承。
校名:学校英文全称
授予学位：本部分将注明获得的具体学位名称。
毕业生姓名：这是最重要的信息之一，标志着该证书是由特定人员获得的。
颁发日期：这是毕业正式生效的时间，也代表着毕业生学业的结束。
其他信息：根据不同的专业和学位，可能会有一些特定的信息或章节。
办理卡尔顿大学毕业证本科学位证成绩单CU学位证【微信：95270640 】价值很高，需要妥善保管。一般来说，应放置在安全、干燥、防潮的地方，避免长时间暴露在阳光下。如需使用，最好使用复印件而不是原件，以免丢失。
综上所述，办理卡尔顿大学毕业证本科学位证成绩单CU学位证【微信：95270640 】是证明身份和学历的高价值文件。外观简单庄重，格式统一，包括重要的个人信息和发布日期。对持有人来说，妥善保管是非常重要的。
DSSML24_tspann_CodelessGenerativeAIPipelines
Codeless Generative AI Pipelines
(GenAI with Milvus)
https://ml.dssconf.pl/user.html#!/lecture/DSSML24-041a/rate
Discover the potential of real-time streaming in the context of GenAI as we delve into the intricacies of Apache NiFi and its capabilities. Learn how this tool can significantly simplify the data engineering workflow for GenAI applications, allowing you to focus on the creative aspects rather than the technical complexities. I will guide you through practical examples and use cases, showing the impact of automation on prompt building. From data ingestion to transformation and delivery, witness how Apache NiFi streamlines the entire pipeline, ensuring a smooth and hassle-free experience.
Timothy Spann
https://www.youtube.com/@FLaNK-Stack
https://medium.com/@tspann
https://www.datainmotion.dev/
milvus, unstructured data, vector database, zilliz, cloud, vectors, python, deep learning, generative ai, genai, nifi, kafka, flink, streaming, iot, edge
Predictably Improve Your B2B Tech Company's Performance by Leveraging Data
Harness the power of AI-backed reports, benchmarking and data analysis to predict trends and detect anomalies in your marketing efforts.
Peter Caputa, CEO at Databox, reveals how you can discover the strategies and tools to increase your growth rate (and margins!).
From metrics to track to data habits to pick up, enhance your reporting for powerful insights to improve your B2B tech company's marketing.
- - -
This is the webinar recording from the June 2024 HubSpot User Group (HUG) for B2B Technology USA.
Watch the video recording at https://youtu.be/5vjwGfPN9lw
Sign up for future HUG events at https://events.hubspot.com/b2b-technology-usa/
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
This webinar will explore cutting-edge, less familiar but powerful experimentation methodologies which address well-known limitations of standard A/B Testing. Designed for data and product leaders, this session aims to inspire the embrace of innovative approaches and provide insights into the frontiers of experimentation!
Recently uploaded (20)
End-to-end pipeline agility - Berlin Buzzwords 2024
End-to-end pipeline agility - Berlin Buzzwords 2024
"Financial Odyssey: Navigating Past Performance Through Diverse Analytical Lens"
"Financial Odyssey: Navigating Past Performance Through Diverse Analytical Lens"
Monthly Management report for the Month of May 2024
Monthly Management report for the Month of May 2024
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
DATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docx
DATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docx
Challenges of Nation Building-1.pptx with more important
Challenges of Nation Building-1.pptx with more important
Predictably Improve Your B2B Tech Company's Performance by Leveraging Data
Predictably Improve Your B2B Tech Company's Performance by Leveraging Data
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
SPSS.ppt
- 1. SPSS (Statistical Package for Social Science) Dr.LILLY GEORGE Head of the Department, Department of Statistics, St. Joseph’s College, Trichy.
- 2. Introduction: What is SPSS? Originally it is an acronym of Statistical Package for the Social Science but now it stands for Statistical Product and Service Solutions One of the most popular statistical packages which can perform highly complex data manipulation and analysis with simple instructions
- 3. The default window will have the data editor There are two sheets in the window: 1. Data view 2. Variable view Opening SPSS
- 4. Scales of Measurement •Nominal Scale - groups or classes Gender •Ordinal Scale - order matters Ranks (top ten videos) •Interval Scale - difference or distance matters – has arbitrary zero value. Temperatures (0F, 0C), Likert Scale •Ratio Scale - Ratio matters – has a natural zero value. Salaries
- 5. Frequencies This analysis produces frequency tables showing frequency counts and percentages of the values of individual variables. Descriptives This analysis shows the maximum, minimum, mean, and standard deviation of the variables Linear regression analysis Linear Regression estimates the coefficients of the linear equation The basic analysis of SPSS that will be introduced in this class
- 6. Frequencies Click ‘Analyze,’ ‘Descriptive statistics,’ then click ‘Frequencies’
- 8. Descriptives The options allows you to analyze other descriptive statistics besides the mean and Std. Click ‘variance’ and ‘kurtosis’ Finally click ‘Continue’ Click Click
- 9. Descriptives Finally Click OK in the Descriptives box. You will be able to see the result of the analysis.
- 10. Click ‘Graphs,’ ‘Legacy Dialogs,’ ‘Interactive,’ and ‘Scatter plot’ from the main menu. Graphs
- 15. Histogram Histogram Really just a bar chart that displays “Num of Cases” only Click “Display Normal Curve” to inspect if your distribution deviates from normal EQ1 5.0 4.0 3.0 2.0 1.0 300 200 100 0 Std. Dev = .86 Mean = 4.3 N = 614.00
- 16. Regression Analysis Click ‘Analyze,’ ‘Regression,’ then click ‘Linear’ from the main menu.
- 18. One-Sample t Test Tests for difference between sample mean and pre-determined population mean Click “Analyze” “Compare Means” “One- Sample T Test…” “Test Value” = Predetermined population mean Options: Exclude Cases Listwise = If multiple variables used, only use cases that have values on ALL variables Exclude Cases Analysis by Analysis
- 19. One-Sample T Test One-Sample Statistics 613 2.83 1.026 .041 EQ2 N Mean Std. Deviation Std. Error Mean One-Sample Test 68.368 612 .000 2.83 2.75 2.91 EQ2 t df Sig. (2-tailed) Mean Difference Lower Upper 95% Confidence Interval of the Difference Test Value = 0
- 20. Independent-Samples t Test Tests if two unrelated samples differ significantly from one another Click “Analyze” “Compare Means” “Independent-Samples T Test…” “Test Variable(s)” = DV “Grouping Variable” = IV Click “Define Groups…” MergeFile1.sav – Male = 1; Female = 0 If IV dimensional, can use cut point to create groups – i.e. x > 7 = Grp 1, x ≤ 7 = Grp 2 Levene’s Test for Equality of Variances If significant, equal variances cannot be assumed
- 21. Independent-Samples t Test Group Statistics 326 4.30 .769 .043 286 4.21 .962 .057 GENDER Female Male EQ1 N Mean Std. Deviation Std. Error Mean Independent Samples Test 5.118 .024 1.203 610 .230 .08 .070 -.053 .222 1.185 543.961 .236 .08 .071 -.055 .224 Equal variances assumed Equal variances not assumed EQ1 F Sig. Levene's Test for Equality of Variances t df Sig. (2-tailed) Mean Difference Std. Error Difference Lower Upper 95% Confidence Interval of the Difference t-test for Equality of Means
- 22. Paired-Samples t Test Tests if two related samples differ significantly from one another Click “Analyze” “Compare Means” “Paired-Samples T Test…” Paired Samples Statistics 4.26 613 .860 .035 2.83 613 1.026 .041 EQ1 EQ2 Pair 1 Mean N Std. Deviation Std. Error Mean Paired Samples Correlations 613 .016 .684 EQ1 & EQ2 Pair 1 N Correlation Sig. PairedSamples Test 1.43 1.327 .054 1.32 1.53 26.657 612 .000 EQ1 - EQ2 Pair 1 Mean Std. Deviation Std. Error Mean Lower Upper 95% Confidence Interval of the Difference Paired Differences t df Sig. (2-tailed)
- 23. THANK YOU