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Related Concept Videos

Expected Value01:15

Expected Value

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The expected value is known as the "long-term" average or mean. This means that over the long term of experimenting over and over, you would expect this average. The expected average is represented by the symbol μ. It is calculated as follows:
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Suppose one wants to test independence between the two variables of a contingency table. The values in the table constitute the observed frequencies of the dataset. But how does one determine the expected frequency of the dataset? One of the important assumptions is that the two variables are independent, which means the variables do not influence each other. For independent variables, the statistical probability of any event involving both variables is calculated by multiplying the individual...
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A goodness-of-fit test is conducted to determine whether the observed frequency values are statistically similar to the frequencies expected for the dataset. Suppose the expected frequencies for a dataset are equal such as when predicting the frequency of any number appearing when casting a die. In that case, the expected frequency is the ratio of the total number of observations (n)  to the number of categories (k).
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A schema is a mental construct consisting of a cluster or collection of related concepts (Bartlett, 1932). There are many different types of schemata, and they all have one thing in common: schemata are a method of organizing information that allows the brain to work more efficiently. When a schema is activated, the brain makes immediate assumptions about the person or object being observed.
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Social psychologists have documented that feeling good about ourselves and maintaining positive self-esteem is a powerful motivator of human behavior (Tavris & Aronson, 2008). In the United States, members of the predominant culture typically think very highly of themselves and view themselves as good people who are above average on many desirable traits (Ehrlinger, Gilovich, & Ross, 2005). Often, our behavior, attitudes, and beliefs are affected when we experience a threat to our...
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Related Experiment Video

Updated: Feb 14, 2026

Dissociation of the Confounding Influences of Expectancy and Integrative Difficulty Residing in Anomalous Sentences in Event-related Potential Studies
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Expecting great expectations when expecting.

Beenish M Chaudhry1

  • 1School of Informatics and Computing, University of Louisiana, Lafayette, LA, USA.

Mhealth
|February 16, 2018
PubMed
Summary
This summary is machine-generated.

Pregnant individuals are increasingly using mobile apps for guidance. A review of the Ovia pregnancy app shows women value its personalized tracking and monitoring features for their pregnancy journey.

Keywords:
Pregnancycommunityinformationpersonalizationtracking

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Area of Science:

  • Reproductive Health
  • Digital Health
  • Human-Computer Interaction

Background:

  • Pregnancy involves significant biological, psychological, and social adjustments for women.
  • Traditionally, maternal and social networks provided guidance for navigating pregnancy changes.
  • The rise of mobile technology has led to the adoption of digital tools for pregnancy support.

Observation:

  • This article reviews the Ovia pregnancy tracking mobile application.
  • User feedback from mothers worldwide was analyzed to understand their experiences.
  • The study focuses on how mobile applications are meeting the need for pregnancy guidance.

Findings:

  • Women appreciate the Ovia app for its ability to track and monitor their pregnancy.
  • The app provides personalized guidance, aiding women in exploring their pregnancy journey.
  • User comments indicate satisfaction with the app's features for managing pregnancy changes.

Implications:

  • Mobile applications like Ovia can supplement traditional sources of pregnancy information and support.
  • Digital health tools offer a scalable solution for personalized maternal care guidance.
  • Further research into user engagement and long-term effects of pregnancy apps is warranted.