The number of gauging cross-sections where a statistically significant decreasing trend was identified. by Krzysztof Kochanek (835532)

Multiple linear regression was used to determine the ratio of similar materials. by Zhengguo Zhu (2676715)

Subjects:

Linear regression of SST from 2004–2019 as a function of time for the MHI and the 12 individual sites across the Main Hawaiian Islands. by Rebecca J. Ward (9872202)

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Inverse exponential curves fitted within the regression analyses of the main parameters of interest. by Eszter Nagy (398278)

Subjects:

Descriptive statistics of main variables. by Dania AL-Najjar (11840857)

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Linear relationship between Simpson’s Diversity and SST. by Rebecca J. Ward (9872202)

Subjects:

S2 File - Factors influencing effective decrease of controlled attenuation parameters in metabolic-associated steatotic liver disease: A multilevel linear regression analysis at Va... by Sonsawan Sangprasert (22772538)

Linear regression coefficients to explain IgG in different age groups. by Hiromi Yamaguchi (2396248)

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Main characteristics of included studies. by Hamed Akbari (8119361)

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Mean values of participants’ heart rate. by Ezel Üsten (16548547)

“…Additionally, a motivational decrease was observed for the high motivation group due to the interruption. …”

Mean values of participants’ heart rate. by Ezel Üsten (16548547)

“…Additionally, a motivational decrease was observed for the high motivation group due to the interruption. …”

Multiple linear regression analysis across generations in test populations. by Gurpreet Kaur Suri (12106975)

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Depleted antibody secreting cells did not result in decreased donor specific antibody in non-sensitized animals. by Natalie M. Bath (6316517)

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Linear regression coefficients. by Helen Sinabulya (11836362)

Linear regression. by Myriam Aïche (22290591)

Boxplot mean cfPWV comparisons. by Johannes Nairz (18010746)

Subjects:

Multiple linear regression. by Gwang Suk Kim (10147342)

The main effects of PRGDP and Gi on SWB. by Feng Huang (62988)

“…Key findings include: (1) In temporal relationships, a 46.70% increase in GDP per capita implies a 0.38 increase in subjective well-being, while a 0.09 increase in the Gini coefficient means a 1.47 decrease in subjective well-being. (2) In spatial relationships, for every 46.70% increase in GDP per capita, subjective well-being rises by 0.51; however, this relationship is buffered by unfair distribution, and GDP per capita no longer significantly affects subjective well-being when the Gini index exceeds 0.609. …”

Backward multiple linear regression of significant factors associated with WHOQOL-BREF. by Umaima Farheen Khaiser (20175798)

“…<p>Backward multiple linear regression of significant factors associated with WHOQOL-BREF.…”

Linear regression model of significant factors affecting positive caregiving appraisal. by Phoebe Abonyo Ouru (21499951)

“…<p>Linear regression model of significant factors affecting positive caregiving appraisal.…”