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 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, 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...
Examples of Descriptive Statistics in a sentence
Table 1: Descriptive Statistics Variable Table 2: Off-shoring of innovation by R&D activity and firm size Share of off-shored innovationNot surprisingly, we find that the propensity to off-shore innovation is a higher for firms with internal R&D.
They include Kolgomorov smirnov goodness of fit test, Run test and Autocorrelation testTable 1: Descriptive Statistics S.E. Skew0.04Range14,910.61Minimum765.73Maximum15,676.34Mean4,820.41Kurtosis(0.78)Variance18,619,391.37Standard Deviation4,315.02S.E. Kurtosis0.07Skewness0.86 Kolgomorov Smirnov Goodness of Fit test is a non parametric test named after two Russian Mathematicians Andrei Nikolaevich Kolgomorov and Nikolai Vasil’evich Smirnov who worked on its development.
Family Variables, Work Variables, and Control Variables: Descriptive Statistics (Nfathers = 1,008; Nmothers = 929) Fathers Mothers Na p value of t test for equality in means of the fathers and mothers.
Descriptive Statistics of Student Groups for Included Cases 40 Table 4.
Any significant reallocation of capital from one unit to another through transfer prices is therefore unlikely.Appendix A-4: Descriptive Statistics This table presents descriptive statistics of the variables used in the paper.
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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 and standard deviations for baseline and daily measures are presented in Table 1.Author ManuscriptMacatee et al. Page 8
Descriptive Statistics. Means and standard deviations, along with the bivariate correlations, are presented in table 1. Means indicate that the youth athletes in the current study experienced the coach as high in autonomy-supportive behavior, and low in controlling behavior. The participants scored higher on competence than on relatedness and autonomy. The mean value for enjoyment was high, indicating that the athletes in the current study enjoyed soccer. Moreover, the scores for performance anxiety were low. Table 2: Descriptive statistics and correlations for the observed variables.Variable M SD Range 1 2 3 4 5 6
Descriptive Statistics. Means, standard deviations and intercorrelations of the observed variables were calculated and are given in Table 1. Values for skewness (ranging from -.69 to -.27) and kurtosis (from -.08 to .95) were also calculated and indicated a normality of distribution. Table 1. Means and standard deviations of and correlations among the observed variables VariableM Note. N = 252 Tran. Lead = Transformational leadership, IDINF = Idealized influence, IMOT = Inspirational motivation, ISTI = Intellectual stimulation, ICON = Individual consideration; Org. Id. = Organizational identification, OIP1- 2 = Two parcels from the Organizational Identification Scale; AUP1-2 = Two parcels from the Basic Psychological Needs Satisfaction in Work Scale; VIG = Vigor, DED = Dedication, ABS = Absorption.*p<.05, **p<.01.
Descriptive Statistics. Means, standard deviations, reliabilities and intercorrelations of all variables are summarized in Table 8.
Descriptive Statistics. MeanSDP10P50P90#Obs.Log (Revenue)14.9571.27313.81614.91416.21394539Log (Employment)2.6980.8531.7922.7733.49794539Log (IT Staff Size)1.0490.6900.0001.0991.09994539GDPR Exposure0.3470.4760.0000.0001.00094539Microservices0.5800.4940.0001.0001.00094539Interoperable0.5590.4970.0001.0001.00094539Avg. # Cloud Vendors2.8740.3492.7412.9962.99994539Intrafirm Vendor Diversity0.0030.0070.0000.0000.01094539
Descriptive Statistics. MeanStd. DeviationNSCCD (Supply Chain Complexity Driver)6.02531.6484279SCA (Supply Chain Activities)3.48101.2796379