Great Salary Survey 2010 - some really webmasters earn? ~ AskPavel
Since I published a few weeks ago the sites coefficients salary survey for 2010, over 150 people from the industry took part and answer the questions. So before I get the results I wanted to thank the contribution of each one of you, this survey may help many who are considering entering the field of SEO as employees and therefore these numbers may provide a snapshot estimated. I consider the survey distri job as a success even though there are hundreds or thousands of participants, since its target audience is relatively small advance (website promoters employees who work in Israel).
Invested a lot of thought and time in the analysis, graphing \ different cuts and presenting information visually clean, but I'm sure there are issues I have not addressed them - you are of course free to comment here and add your own insights. If the information is helpful to you and you would like to share it with friends and colleagues - I am more than happy if you spread the survey, hoping that if it's popular enough to be able to make an annual tradition.
Important to note that this survey for anything (based on a relatively small sample), distri job so do not draw any conclusions from uncertain or facts about the actual salary distri job level. The purpose of the survey is only a snapshot view of the salary estimated coefficients among existing and future sites in Israel. Structure of the 2010 Salary Survey
First of all I should mention that the survey relates only to those who promote sites on search engines, even though played by the same rule dealing with the various online marketing channels (one of the first questions was "What is your main area of work"). The thing is that very few participants indicated distri job other field, so I decided not to count them in statistics that can not be based on such a small amount to draw something.
The survey is divided into 3 main parts: a description of the sample (Descriptive Statistics) - that basically I will present some information about the people who participated in the survey and what percentages of each group. Example, some percentage of attendees are women and some men, what percentage of any age group and so on. These interesting data that reflect our industry in general regardless of salary. Sample analysis - now through the sample presented in the previous section, I will present all sorts of different cuts to examine trends and the influence distri job of certain distri job factors. For example, what is the impact of years of experience on wages? Or the classic question - "Who benefits more men or women? Findings, insights and conclusions - I prefer this part will remain as much open that what is beautiful is no end to diversify the types of conclusions to be drawn.'ll Write some conclusions of my personal, but it is better that everyone will share your opinion about his personal conclusions from the survey - much more interesting. Description of the sample numbers in the following distri job diagrams are percentages -% masculine styled text, but for 2 species.
Now that we have all the data about the participants, it was time to pass the main part - Tacheles, which affects salary and how? I took each parameter questionnaire measuring it using pivot tables (Pivot) to see how it affects wages. The following charts displayed average wages (The Scale Y), ie wages of all wage groups which could choose the original survey. Since there is no equal amount of people per given set of data, I used T Test Excel function (returns the probability associated with). What this function does? If for example I want to compare wages between the two women in front of the 100 men surveyed to understand whether women earn more than men (this is not the case, the numbers are just for example), then one must consider the difference between the sizes of the groups to return more accurate statistics - it just What function T Test makes. Since this is an average, wage scales may not see in all cases all the options wages. This does not mean that no one earning higher amounts than the scale, just like them very small relative to the average. For example, if only one person from survey respondents earning over 40 thousand per month, he simply absorbed averages of several cutouts so that paycheck will not appear. It is important to always go back and check the sample (previous section) when encountering a high number distri job relative to the other numbers in a graph. Perhaps only one percent of all participants indicated that option so it does not really reflect. Most importantly - this survey refers only to sites coefficients employees and self-employed business owners.
Since the attempt is the most commonly used measure of change in wages, I decided to cross it separately versus number of data which are reflected in the graphs at hand (to show a certain tendentious). Crossed my experience with data as a professional distri job course, residential suburbs, student promotion in the international market and thematic relationship between the degree of occupation.
As I said at the beginning of the post, there are endless insights and conclusions that can be drawn these graphs and I prefer to leave the issue open enough for you to bring your ideas snips and interesting conclusions have noticed them. I gathered here a number of conclusions "juicy" than mine, but you are welcome to add comments any conclusion you thought it. Of course it is important to note that this is not solid facts that overall statistics is based on a relatively small sample and there is an equal amount of people in each group, so everything is relative. Men vs Women - I am pleased to note that in the case of SEO invisible discrimination between the sexes. Many times tend to present salary statistics in such a way where the man earns more from the woman, but in this case it seems that the difference is not significant at all. As mentioned, I used the function T Test here I noted earlier it aimed to compare variables of the groups that are not the same size (because that 10% of participants are women). SEO Course - interesting to note the impact of SEO Course salary level. Ostensibly based on two recent charts seems that graduates distri job earn less people studying other education pathways. I believe such a result came out because the courses in Israel is quite new and many webmasters learned and began to deal in this current
Since I published a few weeks ago the sites coefficients salary survey for 2010, over 150 people from the industry took part and answer the questions. So before I get the results I wanted to thank the contribution of each one of you, this survey may help many who are considering entering the field of SEO as employees and therefore these numbers may provide a snapshot estimated. I consider the survey distri job as a success even though there are hundreds or thousands of participants, since its target audience is relatively small advance (website promoters employees who work in Israel).
Invested a lot of thought and time in the analysis, graphing \ different cuts and presenting information visually clean, but I'm sure there are issues I have not addressed them - you are of course free to comment here and add your own insights. If the information is helpful to you and you would like to share it with friends and colleagues - I am more than happy if you spread the survey, hoping that if it's popular enough to be able to make an annual tradition.
Important to note that this survey for anything (based on a relatively small sample), distri job so do not draw any conclusions from uncertain or facts about the actual salary distri job level. The purpose of the survey is only a snapshot view of the salary estimated coefficients among existing and future sites in Israel. Structure of the 2010 Salary Survey
First of all I should mention that the survey relates only to those who promote sites on search engines, even though played by the same rule dealing with the various online marketing channels (one of the first questions was "What is your main area of work"). The thing is that very few participants indicated distri job other field, so I decided not to count them in statistics that can not be based on such a small amount to draw something.
The survey is divided into 3 main parts: a description of the sample (Descriptive Statistics) - that basically I will present some information about the people who participated in the survey and what percentages of each group. Example, some percentage of attendees are women and some men, what percentage of any age group and so on. These interesting data that reflect our industry in general regardless of salary. Sample analysis - now through the sample presented in the previous section, I will present all sorts of different cuts to examine trends and the influence distri job of certain distri job factors. For example, what is the impact of years of experience on wages? Or the classic question - "Who benefits more men or women? Findings, insights and conclusions - I prefer this part will remain as much open that what is beautiful is no end to diversify the types of conclusions to be drawn.'ll Write some conclusions of my personal, but it is better that everyone will share your opinion about his personal conclusions from the survey - much more interesting. Description of the sample numbers in the following distri job diagrams are percentages -% masculine styled text, but for 2 species.
Now that we have all the data about the participants, it was time to pass the main part - Tacheles, which affects salary and how? I took each parameter questionnaire measuring it using pivot tables (Pivot) to see how it affects wages. The following charts displayed average wages (The Scale Y), ie wages of all wage groups which could choose the original survey. Since there is no equal amount of people per given set of data, I used T Test Excel function (returns the probability associated with). What this function does? If for example I want to compare wages between the two women in front of the 100 men surveyed to understand whether women earn more than men (this is not the case, the numbers are just for example), then one must consider the difference between the sizes of the groups to return more accurate statistics - it just What function T Test makes. Since this is an average, wage scales may not see in all cases all the options wages. This does not mean that no one earning higher amounts than the scale, just like them very small relative to the average. For example, if only one person from survey respondents earning over 40 thousand per month, he simply absorbed averages of several cutouts so that paycheck will not appear. It is important to always go back and check the sample (previous section) when encountering a high number distri job relative to the other numbers in a graph. Perhaps only one percent of all participants indicated that option so it does not really reflect. Most importantly - this survey refers only to sites coefficients employees and self-employed business owners.
Since the attempt is the most commonly used measure of change in wages, I decided to cross it separately versus number of data which are reflected in the graphs at hand (to show a certain tendentious). Crossed my experience with data as a professional distri job course, residential suburbs, student promotion in the international market and thematic relationship between the degree of occupation.
As I said at the beginning of the post, there are endless insights and conclusions that can be drawn these graphs and I prefer to leave the issue open enough for you to bring your ideas snips and interesting conclusions have noticed them. I gathered here a number of conclusions "juicy" than mine, but you are welcome to add comments any conclusion you thought it. Of course it is important to note that this is not solid facts that overall statistics is based on a relatively small sample and there is an equal amount of people in each group, so everything is relative. Men vs Women - I am pleased to note that in the case of SEO invisible discrimination between the sexes. Many times tend to present salary statistics in such a way where the man earns more from the woman, but in this case it seems that the difference is not significant at all. As mentioned, I used the function T Test here I noted earlier it aimed to compare variables of the groups that are not the same size (because that 10% of participants are women). SEO Course - interesting to note the impact of SEO Course salary level. Ostensibly based on two recent charts seems that graduates distri job earn less people studying other education pathways. I believe such a result came out because the courses in Israel is quite new and many webmasters learned and began to deal in this current
No comments:
Post a Comment