1. Effect Size (p. 256) – the difference between 2 groups – The difference between the number of male participants compared to the number of female participants was within relevance and therefore did not influence the results.
2. Analysis of Variance (ANOVA) (p. 260) – compares the mean of 2 or more groups – An ANOVA was performed to reduce the likelihood of an error due to low number of intervention sessions.
3. Analysis of Covariance (ANCOVA) (p. 265) – used to adjust the difference between the pretest scores of two or more groups – A series of ANCOVAs were performed to compare the child’s chronological age and gender.
4. Case Study (p.279) – in-depth analysis of a single experience or entity in its natural setting – The case study of the …show more content…
Category (p. 299) – ideas coded similar to form a representation of the same data – Three categories of sensory features include hyporesponsiveness, hyperresponsiveness, and sensory seeking.
8. Codes (p. 298) – used to organize data into categories – Verbal utterances, phrases, and/or complete sentences are codes for expressive language.
9. Margin of Error (p. 98) – indicates the interval of error within a population value – When comparing children with autism to children of typical development and their sensory processing patterns, the margin of error is +2/-2.
10. Cluster Sampling (p. 102) – randomly selecting naturally occurring groups – The four boys were randomly selected to participate in a survey for the 4th grade student population.
11. t-test (p. 258) – compares the means of 2 groups – The t-test compared hyperresponsiveness and hyporesponsiveness
12. Brief Notes (p. 289) – detailed records of observation which will be expanded on later – During the caregiver interview, the researcher documented the participants’ responses to expand on in the report.
13. Single-subject design (p. 238) – recorded behavior of an individual before and after a new intervention or procedure – Researchers chose a single-subject design as their method to investigate a new intervention to improve receptive language
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Following the second part of Ellis’s framework (2013), going onto the core research issues the introduction and background to the study does identify the need for research to be done, the purpose of the research can be identified. It states in the abstract that the aim of the study was to offer a thorough report of the experience people go thorough when they have to make a decision on placing a family member into a special care unit among a diverse sample of carers. To achieve maximum variation
A power analysis indicated the need for 40 subjects per group in order to provide 80% power so that it can well detect differences between the two groups. These differences were detected by using a
The single- subject design was used because the researcher paired the students to compare the students that received treatment in comparison to the students that did not receive treatment (Whitfield, 1999).
In this study, t= -3.15 describes the mental health variable. It is significant because they are the variables being tested since the p value is 0.002 and the alpha is 0.05, the difference can cause the null hypothesis to be rejected.
A researcher has designed a study to test the effects of different types of individual psycho-therapy on people's levels of anxiety. She has randomly placed people into one of three groups: a behavioral treatment group, a psycho-dynamic treatment group, or a no-treatment control group. She then measures people's level of anxiety after the treatment.
However, treatment four, 0.1296 (±0.608), represents that the mean was extraneous from what it should be (Table 1). The t-tests show how different the mean is in each treatment.
In Analysis of variance (ANOVA) is a group of statistical sample used to resolve the differences between group means and their connected steps like variation between groups. The observed variance in a specific variable is divide into components attributable to various fountain of variation.
The t score that represents the greatest relative difference between pretest and 3 months is t = 4.14. The results of the analyses indicate that this is a statistically significant result, with p < .05.
| Based on explicit knowledge and this can be easy and fast to capture and analyse.Results can be generalised to larger populationsCan be repeated – therefore good test re-test reliability and validityStatistical analyses and interpretation are