Education and statistics

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A Framework for Assessing the Quality of Education Statistics

A Framework for Assessing the Quality of Education Statistics

i. The timeliness of statistics follows internationally accepted good practices. There is a regular dialogue between the area within the education ministry responsible for statistics (including the administrative school census, and where applicable other elements such as assessments of student achievement) and the policy area of the ministry on the statistical information needed for policy purposes, on the preparation and implementation of plans for improvements as needed, and on the use of statistical information for policy purposes.

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NATIONAL CENTER FOR EDUCATION STATISTICS

NATIONAL CENTER FOR EDUCATION STATISTICS

The National Center for Education Statistics is pleased to provide you with your institution’s annual IPEDS Data Feedback Report. The report compares data provided by your institution in 2008-09 through the Integrated Postsecondary Education Data System (IPEDS) to data for a similar group of institutions. Like last year, your institution was given the opportunity to select its own comparison group. We strongly encourage institutions to take advantage of the opportunity to select the other institutions to which they want to be compared in the report, as they generally find the report more informative. If your institution did not submit its own group, IPEDS identified a comparison group for you (see the list toward the back of this report for the institutions in your comparison group).
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Education and training statistics for the United Kingdom : 2014

Education and training statistics for the United Kingdom : 2014

HM Treasury provided education expenditure figures in Annex A from their Public Expenditure Statistical Analysis (PESA). Education expenditure is defined here as under fives, primary education, secondary education, post-secondary non-tertiary education, tertiary education, subsidiary services to education, research and development education and education not elsewhere covered. This is based on the UN Classification of the Functions of Government (COFOG) and is a sub-set of the education and training category. Training expenditure is not included. Total Expenditure on Services (TES) is a definition of aggregate public spending and covers most expenditure by the public sector that is included in Total Managed Expenditure (TME), where TME is a measure of public sector expenditure drawn from components in national accounts produced by the Office for National Statistics (ONS). TES broadly represents the sum of current and capital expenditure of central and local government, and public corporations, but excludes general government capital consumption and other accounting adjustments.
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Projections of Education Statistics to 2022

Projections of Education Statistics to 2022

NOTE: Race categories exclude persons of Hispanic ethnicity. Because of underreporting and nonreporting of racial/ethnic data and nonresident aliens, some estimates are slightly lower than corresponding data in other published tables. Enrollment data in the “race/ethnicity unknown” (all years) and “two or more races” (2008 through 2011 only) categories of the IPEDS “Enrollment component” have been prorated to the other racial/ ethnic categories at the institutional level. Mean absolute percentage errors of selected education statistics can be found in table A-2, appendix A. Some data have been revised from previously published figures. SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System (IPEDS) “Fall Enrollment Survey” (IPEDS-EF:97–99); IPEDS Spring 2001 through Spring 2012, Enrollment component; and Enrollment in Degree-Granting Institutions by Race/Ethnicity Model, 1980–2011. (This figure was prepared February 2013.)
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GENDER-SENSITIVE EDUCATION STATISTICS AND INDICATORS

GENDER-SENSITIVE EDUCATION STATISTICS AND INDICATORS

III. GENDER ISSUES IN DATA AND INDICATORS ON LITERACY AND EDUCATION Gender issues can be considered with reference to different kinds of data sets. At the simplest level one can consider the absolute figures and the absolute difference between the numbers of male and female illiterates, pupils, students, teachers, etc. Similar considerations can be applied to derived statistics in the form of indicators such as literacy rates, admission rates, enrolment ratios, school survival and so on. At a more sophisticated level one can use specific gender-disparity indicators as well as multivariate statistical methods for the purposes of a more in-depth analysis.
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Education : historical statistics : November 2012

Education : historical statistics : November 2012

The organisation of every stage of education has undergone significant change over the last century. These changes have fundamentally altered most aspects of education. Historical indicators are therefore particularly interesting, but also problematic. Very few series are consistent over more than a few decades. The definition/size of different stages of education (primary, secondary, further/higher), school leaving ages and examinations have changed markedly as have state organisation and funding. As key concepts in education change so do the types of statistics collected. The increased role of the state in the first half of the 20 th century also widened the scope of official education statistics.
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Higher education finance statistics

Higher education finance statistics

Much of the information in this note is taken from the annual Higher Education Statistics Agency (HESA) publications Resources of higher education institutions and its recent replacements. A limited amount of free information can be found on the HESA website. The most recent Patterns and Trends in UK Higher Education from Universities UK looks at 10 year trends in the sector and variations between institutions on a number of different indicators. The Higher Education Funding Council for England publishes an annual financial assessment of the sector in England. The latest version is Financial health of the higher education sector: 2012-13 financial results and 2013-14 forecasts.
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Chapter 1. Introduction of Inferential Statistics for Education; 2020.doc

Chapter 1. Introduction of Inferential Statistics for Education; 2020.doc

Education in statistics deals with evidence-based reasoning, particularly with data analysis. Therefore, education in statistics has strong similarities with education in empirical disciplines such as psychology, in which education is closely linked to "practical" experimentation. It specifically helps in the assessment which leads to the improvement of teaching and learning statistics at all levels of education. The applications of basic statistical concepts in real life which aims to solve problems found in educational research and related policies. The focus is on understanding how to use and interpret the statistical procedures commonly used in quantitative research with the help of statistical software to aid in data analysis
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Higher education finance statistics

Higher education finance statistics

Much of the information in this note is taken from the annual Higher Education Statistics Agency (HESA) publications Resources of higher education institutions and its recent replacements. A limited amount of free information can be found on the HESA website. The most recent Patterns and Trends in UK Higher Education from Universities UK looks at 10 year trends in the sector and variations between institutions on a number of different indicators. The Higher Education Funding Council for England publishes an annual financial assessment of the sector in England. The latest version is Financial results and TRAC outcomes 2014-15, forecasts are given in Financial health of the higher education sector: 2015-16 to 2018-19 forecasts
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Antecedents of Statistics Anxiety in a Higher Education System

Antecedents of Statistics Anxiety in a Higher Education System

Statistics anxiety is a pervasive problem in many fields of study (Macher, et al., 2012). Onwuegbuzie et al., 2003 highlight different areas like education, psychology, sociology as some of the courses where it is prevalent. It is, therefore, no doubt that most students from areas struggle with statistics related courses such as research methodology and statistical methods as Statistics are all pervaded. Its applications have increased in recent years (Onwuegbuzie, et al., 2003) as it has permeated into different fields. Statistics is a means to the end not a goal in itself. It is used in research to come to conclusions. In academics, statistics play an essential role as it assists students in undertaking empirical studies (Coetzee and Van der Merwe, 2010). It is worth noting that statistics anxiety will, therefore, cripple academic development as well as living life. It applies to workplaces, shopping malls, sports, accounts (Chew and Dillon, 2014). Therefore the importance of statistics cannot be underestimated. The universe’s language is statistics. It is the water and salt of education, research, and development.
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Education and training statistics for the United Kingdom : 2014

Education and training statistics for the United Kingdom : 2014

In England, public provision of secondary education in an area may consist of a combination of different types of school, the pattern reflecting historical circumstance and the policy adopted by the local authority. Comprehensive schools largely admit pupils without reference to ability or aptitude and cater for all the children in a neighbourhood, but in some areas they co-exist with other types of schools, for example grammar schools. Academies, operating in England, are publicly funded independent schools. Academies benefit from greater freedoms to help innovate and raise standards. These include freedom from local authority control, the ability to set their own pay and conditions for staff, freedom around the delivery of the curriculum and the ability to change the lengths of terms and school days. The first academies opened in 2002 with the objective of replacing poorly performing schools. Academies were established and driven by external sponsors, to achieve a transformation in education performance. The academies programme was expanded through legislation in the Academies Act 2010. This enables all maintained primary, secondary and special schools to apply to become an academy. Schools that are performing well are able to become academies without a sponsor. The first of these academies opened in September 2010 and are expected to work with
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Education Statistics Bulletin

Education Statistics Bulletin

New undergraduate enrollments for the Fall are mainly in the social sciences (22 to 24%), followed by the applied sciences (15 to 18%) while the administration and education sciences occupy third place (14%). Applied sciences remains a field of study which few women choose, although female representation has considerably increased since 1992, from 25 to 30%. At the other end of the spectrum, relatively few men are interested in health sciences–barely 25% of enrollments.

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National Cooperative Education Statistics System

National Cooperative Education Statistics System

Because of their different perspectives on the data, the data source (e.g., an education agency) and data user (e.g., a researcher from an institution of higher education) may have competing business rules for a single data set. For example, if an SEA collects data from LEAs and then provides those data to a university research project, the SEA, as the data provider, will have business rules for collection, transformation, and loading the data into its system, as well as for generating and sharing output from the system. The output rules may include parameters for disaggregation and cell suppression if the use does not permit the disclosure of personally identifiable data. Similarly, the research project or policy analyst (i.e., the researcher who uses the data) may establish another set of business rules for the data set as they relate to the policy or research question being studied. Best practices suggest that the data provider and data user engage in a dialogue that clarifies any assumptions and limitations related to their respective application of business rules.
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On criminal statistics; especially with reference to population education and distress in Ireland

On criminal statistics; especially with reference to population education and distress in Ireland

theless, a still farther reduction of 23,92,$, having taken place in the following year, when the number relieved fell to the minimum in the decennial period, the number who emigrated ag[r]

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Education Across the European Union: Statistics and Indicators:1998

Education Across the European Union: Statistics and Indicators:1998

et graphiques LEJ: Taux de scolarisation par âge et sexe CITE 0-7 Taux de scolarisation par âge et sexe dans l'enseignement pre-primaire CITE 0 Taux de scolarisation par âge et sexe dans[r]

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2010 Statistics on Social Work Education in the United States A SUMMARY

2010 Statistics on Social Work Education in the United States A SUMMARY

I n 2010, 395 social work programs provided individual infor- mation about 3,638 full-time faculty members. For the pur- poses of this report, full-time refers to faculty who spent 50% or more of full-time employment (FTE) in social work education. Ninety-five records were excluded from analysis because the partici- pants responded “part-time” to the question “During the Fall 2010 term, did the institution consider this faculty member a full-time appointment or part-time appointment?” Twenty surveys were ex- cluded from analysis because the participants gave percentages less than 50% for the total FTE assigned to social work program levels or other social work activity, or they gave percentages greater than 50% for FTE worked in units outside social work.
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Syllabus. Inferential Statistics to Education, Undergraduate; 2019, 1.doc

Syllabus. Inferential Statistics to Education, Undergraduate; 2019, 1.doc

Solve the Quiz you have given in first class. In the next class, at random, some students will work out the exercises on the board. The objective of this quiz is that the student refreshes the knowledge and skills acquired in Descriptive Statistics, since it is important to understand Inferential. Download Chapter I of the lecture notes (posted on the course web site)

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Statistics in Focus: Population and social conditions  Education in Europe Key statistics 2000/01  2003 13

Statistics in Focus: Population and social conditions Education in Europe Key statistics 2000/01 2003 13

Number of pupils and students ISCED levels 0-6 - D, RO, SI, AL, MK: Data exclude ISCED level 6 - L: Luxembourg does not have a complete university system most students study abroad - PT,[r]

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Statistics in Focus: Population and social conditions  Education in Europe Key statistics 2002 2003  2005 10

Statistics in Focus: Population and social conditions Education in Europe Key statistics 2002 2003 2005 10

,Θ ΩΚΗ ΞΥΡΣΗ∆Θ 8ΘΛΡΘ, Η[ΣΗΘΓΛΩΞΥΗ ΡΘ ΗΓΞΦ∆ΩΛΡΘ∆Ο ΛΘςΩΛΩΞΩΛΡΘς Ζ∆ς, ∆Ω 89.4%, Ο∆ΥϑΗΟ∴ ΙΞΘΓΗΓ Ε∴ ΣΞΕΟΛΦ ςΡΞΥΦΗς ΦΗΘΩΥ∆Ο, ΥΗϑΛΡΘ∆Ο ∆ΘΓ ΟΡΦ∆Ο ΟΗΨΗΟς ΡΙ ϑΡΨΗΥΘΠΗΘΩ.. ,Θ 3 ΦΡΞΘΩΥΛΗς ΠΡΥΗ ΩΚ∆Θ [r]

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Education Across the European Union: Statistics and Indicators  1995

Education Across the European Union: Statistics and Indicators 1995

Sekundarstufe II ISCED 3 Upper secondary education ISCED 3 Education secondaire supérieur CITE 3 Tertiärbereich ISCED 5,6,7 Higher education ISCED 5,6,7 Education supérieur CITE 5,6,7.. [r]

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