Descriptive Statistics. Means of the measures appear in Table 1. Cronbach’s alphas for the measures were adequate (≥ .78) and resembled those of prior studies (e.g., Mushquash & Sherry, 2012).
Descriptive Statistics. Means, standard deviation as well as the correlation matrix associated with the variables in this study are presented in Table 1. Table 1Descriptive data (means and standard deviations) and intercorrelation amongst the variablesVariables* p<0.05 4.1.2 Individual levelAt the individual level, in the past six months respondents were on average involved simulta- neously in 3.54 project teams (with a standard deviation of 3.12). The respondents are mainly male (76.7 per cent) and most of them are educated at a post-graduate level (average education level is close to 3). The average project experience that the respondents have is8.71 years, but a large range exists (standard deviation of 8.55 years). Of the three skills measured, the respondents on average possess high cognitive skills (mean value of 4.12), followed by social skills (mean value of 3.96) and emotional skills (mean value of 3.70). When respondents self-rated their innovative performance, the average score is 5.28 (on a 7 points Likert scale).Correlation statistics indicate that the emotional, cognitive and social skills have positive and statistically significant linear relationships with individual innovative performance (r of 0.291,0.285 and 0.174 respectively). Correlations were found amongst the skills: emotional skill correlates with cognitive skill with correlation coefficient (r) of 0.396; and social skills correlate with emotional skill (r=0.391) as well as cognitive skill (r=0.268). The variable of interest in this study, i.e. number of MTM, correlates positively with age (r=0.216) and project experience (r=0.168). It is not surprising that age and project experience have a strong and positive relationship (r=0.752). The size of the correlation coefficient reported above allows for the conclusion that no multi- collinearity problems exist in our data.4.1.3 Project team levelAt the project team level, the average of team tenure is 18.27 months with a standard deviation of 11.67 months. On average, there are 9 core team members per project team. The diversity of teams is viewed in terms of separation in team tenure (standard deviation of team tenure of the team members in a team) and separation in education level (i.e. standard deviation of education level of the team members in a team). Looking at the separation of team tenure, the average is 10.59 months; whereas the education separation has a mean value of 1.29. This means that teams consist of team members who are diverse in term of th...
Descriptive Statistics. Means and standard deviations for the three training candidate groups on the domains and facets are shown in Table 1. The NEO PI-R manual provides the following score ranges based on general population norms: “very low” [T ≤ 34], “low” [T = 35-44], “average” [T = 45-55], “high” [T = 56-65], and “very high” [T ≥ 66] [27].
Examples of Descriptive Statistics in a sentence
Descriptive Statistics: Measures of central tendency, variability, deviation from normality, size and stability.
Table 2: Descriptive Statistics for IFLS 1993 and 2000 Sample VariableN=4797Note: Sample is individuals between the age of 15-55 in 1993 and earning income in 1993.
Estimation of Descriptive Statistics for Multiply Censored Water Quality Data.
Descriptive Statistics for Cardiovascular Functioning over Successive Experimental Phases for Women and Men 90Table 13.
Table of Descriptive Statistics for Subjective Task Ratings 93Table 14.
More Definitions of Descriptive Statistics
Descriptive Statistics. Means and standard deviations for all study variables are presented in Table 3. The results show that takeovers destroy value for shareholders of acquiring firms in France. The cumulative abnormal returns (CARs) averages observed around the announcement date are negative and different from zero at the 5%. These results confirm those obtained by previous studies of French and Langhor Eckbo (1989), and Sanssenou Charlety-Lepers (1994), Mezz (1997) and Vandelanoite (2002), Sbai (2010), but generally different from those obtained by American studies document a positive abnormal return by the shareholders of the acquiring firm (Moeller et al.2004; Masulis and al.2007). However, our results are consistent with those obtained from studies of M&A in the European context (Campa and Hernando, 2008) where shareholders of acquiring firms an average negative abnormal return around the announcement dates. As proposed by Berkovitch and Narayanan (1993), the observation of negative abnormal returns suggests that takeovers initiated by firms in our sample are motivated by the ambition of leaders. However, the returns obtained by shareholders may vary from one company to another depending on the characteristics of the acquiring company or by characteristics of the transaction.Table 3 also presents statistics on characteristics of acquisition transactions. Half of these acquisitions occurred between 1999 and 2000, these acquisitions are mostly friendly nature (95%), and these acquisitions are characterized by a diversification in terms of industry sector and low near the involved parties. The acquiring firms use in 59% of the payment in cash as a mode of financing. These
Descriptive Statistics. Means and standard deviations for the latent variables are reported in Table 3. To compute these descriptive statistics, multiple-item scales were summed and averaged. The means of all the variables lie between 4.5 and 5.5. Standard deviation values are less than +1.50. Hence, the descriptive statistics obtained in this study is acceptable. The correlations between the variables are shown in Table 4. ConstructMeanStandard DeviationWebsite Usefulness5.271.03Interface Quality4.891.12Information Quality5.300.89Pre-order Service Quality5.330.88User Satisfaction5.190.95Intention of Planned Purchase4.961.29Table 3. Descriptive Statistics WebsiteUsefulnessInterfaceQualityInformationQualityServiceQualityWebsiteUsefulness1.00 InterfaceQuality0.63481.00 InformationQuality0.62290.67491.00 ServiceQuality0.67370.64720.69191.00 Table 4. Correlation Matrix
Descriptive Statistics. Means, standard deviations and internal consistency scores of the measures used in the study are presented in Table 2. The intercorrelations among the study variables are presented in Table 3. Table 2.Means, standard deviations and internal consistency scores (Ν = 1040) MeanEffort4.37 Table 3.Intercorrelations among the study variables (Ν = 1040) 12345678910111213141516171819202122231. Doping Intentions- 2. Mastery-approach-.12 The results of the descriptive analyses indicated that 8.2% of the participating athletes reported past use of prohibited PED. Specifically, 3.7% reported PED use only once in the past, 3% said they used prohibited PED occasionally, whereas 1.5% reported systematic use of prohibited substances (Figure 2). Figure 2. Percentage of athletes having occasionally or systematically used prohibited substances In addition, the results of descriptive analyses indicated that only a small percentage of athletes reported high intentions to use prohibited substances in the future (Figure 3, Figure 4 and Figure 5). Figure 3. Intention to use prohibited substances Figure 4. Belief to use prohibited substances
Descriptive Statistics. Means and standard deviations associated with the variables under study are presented in Table 2. The mean scores for all eight items of absorptive capacity are above the mid-point of 3 (on a scale of 1 to 5); this shows that firms possess an above-satisfactory level of absorp- tive capacity. On average, NTBFs access intended knowledge from about 10 partners formally and about 37 partners informally. The average of the knowledge spillover score is close to 1.5 on a scale of 5, showing that, on average, NTBFs “rarely” to “sometimes” search in this mode. About 46 per cent of the firms in the sample are located in a science park location. NTBFs report that, on average,42.12 per cent of their sales come from innovated products and services which are technologically improved to the firm, whereas about 30 per cent of sales were generated with products or services that were technologically new to the firm. The average score for the scope of innovation outcomes (i.e. technical performance owing to innovations) is 3.68, indicating a relatively high level. The averages of firm age and size are 5.13 years and9.25 employees respectively. This shows that the sample firms are young and small. Table 2Means and standard deviationsVariablesMeanStd. dev.Independent variables:Absorptive capacity item 14.230.899Absorptive capacity item 23.311.213Absorptive capacity item 33.061.290Absorptive capacity item 43.731.012Absorptive capacity item 53.940.802Absorptive capacity item 63.871.205Absorptive capacity item 73.601.107Absorptive capacity item 83.731.206Intended knowledge transfer through formal relationships (number)9.7512.516Intended knowledge transfer through informal relationships (number)37.49 The items of ‘absorptive capacity’ were entered in a principal component factor analysis that produces a two-factor solution (KMO = 0.655; Bartlett = 70.411; p = 0.000).Table 3 shows that absorptive capacity items 3, 2 and 5 loaded onto a factor that can be named‘absorptive capacity for incremental inno- vations’; whereas the second factor containing items 1, 6, 7 and 8 can be labeled ‘absorptive capacity for new innovations’. Note that item 6 is not loading onto any of the two factors and is therefore excluded. Table 3Factor analysis for absorptive capacity
Descriptive Statistics. Means and Standard Deviations are used to describe the respondents’ lifestyle based on their activities, interests, and opinion.
Descriptive Statistics. Means, mean scale scores, standard deviations, coefficient alphas (where appropriate), and correlations between the study variables are shown in Table 4. Coefficient alphas for the organizational memory subscales ranged from .77 to .89, again indicating acceptable to excellent internal consistency estimates (DeVellis, 2003). As with Part 1, and proposed in Hypothesis 4, correlations were expected between the organizational memory subscales and the tenure variables. All of the organizational memory factors correlated with organizational tenure, while only job knowledge and history correlated with job tenure. Industry knowledge along with job knowledge and history correlated with industry tenure.Table 4. Part 2 CFA Descriptive statistics and correlations. M SD α * p < 0.05 level; **p < 0.01 level, *** p < 0.001 level, (two-tailed).
Descriptive Statistics include: the means, or averages for a set of data; standard deviation, or amount of variation in the data; and ranges, or differences between the lowest and highest values in the data. These were calculated for continuous variables. “Continuous variables” are values that can fall anywhere within the data range, for example, the number of seconds participants take to wash their hands. Frequencies were calculated for categorical variables – where the data falls under a label, or category, for example, the number of participants who are sanitiser-users. One-way analysis of variance (one-way ANOVA) was performed, which a technique is used to assess differences between unrelated groups of data.