Sentences with phrase «score analysis data»

The score analysis data is great to review when trying to determine what kind of reach and influence you have.

Not exact matches

One of my favorite keyword tools out there, Jason and CCarter understand search and data analysis and put a lot of time into building a truly powerful keyword suite with some robust scoring.

Our products include live odds, scores, public betting trends data, as well as unique betting systems analysis.

«Our data indicate that head trauma events can be effectively identified by K - D test time scores, and that analyses of this new measure in future studies can establish its role as a rapid sideline screening test for concussion,» she writes.

In a secondary analysis, the NSLY found that the achievement scores of children breastfed for at least 29 weeks were 1.5 points higher than those of children never breastfed (P =.01), but the authors considered their data about breastfeeding duration «less reliable» than data about whether a child was ever breastfed.

The authors used other birth - certificate data on maternal coexisting conditions to adjust for high - risk conditions and performed a propensity - score analysis to account for the perinatal mortality associated with planned out - of - hospital birth versus hospital birth.

In their analysis of data from 1423 Swedish women who were studied from 2.5 to 12 mo postpartum, lactation score was significantly associated with weight retention, but it explained little of the variance in PPWR.

Because the drugs are illegal and data is extremely difficult to obtain, the participants relied on their collective knowledge and experience to score the drugs and a decision analysis model to aggregate the judgments.

For the new analysis — the first of its kind — the research team looked at dietary data from 160,191 women and assigned inflammation scores based on 32 food components that the women reported consuming in the three months prior to their enrollment.

ÜberResearch and Altmetric, leading data and analytics companies serving scientific funders and research organizations, have published an analysis of Parkinson's disease research papers with the highest Altmetric Attention Scores in the Journal of Parkinson's Disease.

The scores were converted to a zero to 100 scale for the data analysis.

For example, he recently posted data on the NIGMS blog on how peer - review scoring works and a much - discussed analysis suggesting that midsize labs are the most productive.

After analysis, the images will be preserved alongside the subject's clinical data, including genetic information and scores on cognitive tests.

And analysis of data gathered by the experiments there will continue for years after the collider itself is switched off, potentially leaving the door open for the outgoing giant of the physics world to deliver one last big score.

The scoring system is based on an analysis of large genomic datasets and patient data, and it could eventually be developed for clinical use.

«A subgroup analysis that combines data from children in both the single - and multiple - dose studies demonstrated a mean 5 point increase in muscle function score in children who received at least 9 mg of ISIS - SMNRx between the ages of two and 10 who did not have severe scoliosis or baseline HFMSE scores at the extreme low or high ends of the scale.

The score is based on a 12 - gene signature identified through analysis of large genomic datasets and clinical patient data.

Data analysis suggested that emotional intelligence (EI) was a significant predictor of information literacy scores: the more EI a person had, the higher his or her information literacy score.

We include 2002 as a pre-NCLB data point in our analysis because, given the timing of the passage and implementation of the law, it seems unlikely that spring 2002 scores could have been substantially influenced by NCLB (see sidebar).

We conducted our analysis alternately using absolute student achievement, measured with statewide mean SAT scores for the 1989 — 90 school year and the mean high - school dropout rate calculated from 1990 census data, and with a second measure that represents the deviation of actual achievement from expected student performance.

This strategy isn't perfect, but a validation analysis using the 2011 and 2013 data showed that it produces estimated adjusted scores that are very highly correlated (r = 0.97) with the actual adjusted scores.

Still, even a modicum of school choice and competition can boost student test scores, especially when combined with a comprehensive examination system for high - school graduates, says Ludger Woessmann, whose systematic, sophisticated analyses of international test - score data best summarize what can be learned from abroad.

It's time for HODs to do data analysis and you might find that your A level ALPS score isn't as good as you had hoped.

Official policy statements indicate that inspectors place substantial weight on test scores, which is borne out by analysis of the data.

The initial government evaluation gathered data through 2008 - 09, so the graduation rate analysis is only based on about 300 students (as compared to 1,300 students from multiple grades included in the test - score analysis).

We restrict our analysis to students whose PSAT / NMSQT scores are within 15 points on either side of the cutoff, to produce a data set of approximately 58,000 students across all years.

The second study (hereafter the «meta - analysis»), by Credé et al., [iii] is a systematic review of data from all the published studies that could be found in which participants who were at least of middle school age and in which correlations were reported or could be calculated between scores on any of Duckworth's grit scales and other variables.

A detailed analysis means that an app will be storing all the data about you, such as how much of your syllabus is completed, what topics you have searched, how many online tests you have taken and what your scores are in those, or how was your ranking among all.

Our analyses were based on the approximately 125,000 students in grades four through seven within these districts who completed the surveys in spring 2015 and whose responses we can link to data on test scores in grades three through eight from spring 2013 to spring 2016.

For purposes of this analysis, we constructed a data set that contained pupil - level test scores for about 220,000 students.

The analysis extends previous work (see «Johnny Can Read... in Some States,» features, Summer 2005, and «Keeping an Eye on State Standards,» features, Summer 2006) that used 2003 and 2005 test - score data and finds in the new data a noticeable decline, especially at the 8th - grade level.

In our analysis, there are 68,677 students for whom the data allow us to compute at least two gain scores in math (and a similar number for the reading estimation).

Our analysis is based on statewide, student - level longitudinal data obtained from the Arizona Department of Education (AZDOE) that contains information on test scores, school enrollment, and student characteristics for the 2005 - 06 through 2011 - 12 school years.

When ELL students are not isolated in these low - achieving schools, their gap in test score results is considerably narrower, according to a Pew Hispanic Center analysis of newly available standardized testing data for public schools in the five states with the largest numbers of ELL students.

An analysis of national and metropolitan data on public school populations and state standardized test scores for 84,077 schools in 2010 and 2011 reveals that:

The observational analysis looks at middle and high schools only because there are no baseline score data for elementary school students.

This study presents evidence on whether NCLB has influenced student achievement based on an analysis of state - level panel data on student test scores from the National Assessment of Educational Progress (NAEP).

Kane's 2013 analysis, which was presented at the trial (pdf), looked at several years of data as teachers moved between schools and found that Chetty's model could accurately identify ineffective teachers and the impact they had on their students» test scores.

Prior analyses of assessment data uniformly indicate that ELL students are much less likely than other students to score at or above proficient levels in both mathematics and reading / language arts.

For most of the analysis, I use a data set created by pooling the observations from all four years for a total of 23,883 observations with math scores and 23,544 with reading scores.

While complete data were not available for any other year, we repeated this analysis with the Class of 2012 using 10th - grade test scores to control for differences in student ability and found, reassuringly, a similar pattern.

Imbalance scores for Hispanics, Asians, and Others are excluded from the analysis underlying the figure because school choice policies are very weakly related, if at all, to imbalance scores for these groups in the present data.

This is why, in our modeling efforts, we do massive multivariate, longitudinal analyses in order to exploit the covariance structure of student data over grades and subjects to dampen the errors of measurement in individual student test scores.

In addition, statistical analysis of the PALM data revealed that all three components of PALM (classroom - embedded, on - demand, and taking a closer look) contributed significantly to the prediction of students» scores on a norm - referenced reading test.

In a few districts, district and school leaders reported that analysis of trend data by district and / or state assessment specialists had led to the identification of early indicators of students academically at risk, based on test scores or other factors (e.g., family circumstances), in lower grade levels.

In 2012, a pair of analyses published by Harvard University's Strategic Data Project found that the students of Board - certified teachers in the Los Angeles Unified School District and in Gwinnett County, Georgia, outperformed their peers by approximately two months in math and one month in English Language Arts, based on gains in student test scores.

What reformers should do is develop the tools that can allow families to make school overhauls successful; this includes building comprehensive school data systems that can be used in measuring success, and continuing to advance teacher quality reforms (including comprehensive teacher and principal evaluations based mostly on value - added analysis of student test score growth data, a subject of this week's Dropout Nation Podcast) that can allow school operators of all types to select high - quality talents.

In our analyses of Florida data, 37 percent of the variation in students» middle school course tracks can be explained by a combination of their prior test scores, race / ethnicity, and family income.

This corresponds with Dropout Nation «s analysis of NAEP data, which shows that average reading and math scores for top - performing students improved between 2002 and 2011 (versus almost no change between 1998 and 2002, before No Child was implemented), while the percentage of students reaching such levels increased since its passage (including a four percentage point increase in the number of students reaching such levels in reading between 2002 and 2013).

The Naiku platform allows educators to create, share, import and deliver rich standards aligned quizzes and tests in any subject area, using graphics, multimedia clips and hyperlinks to query students with multiple item types.With automated scoring and built - in analysis tools, teachers can inform and differentiate instruction within the classroom, and data can be shared across the school and district to enhance best practices.